[1] "ofn"        "-oTESCA-TP"
[1] "opt"                    "-OPAGGREGRATED_CLUSTER"
[1] "tl" ""  
[1] "dx" ""  
[1] "opt"                 "AGGREGRATED_CLUSTER"
[1] "dx" ""  
[1] "cfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/ESCA-TP/22506419/ESCA-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/ESCA-TP/22541001/ESCA-TP.mergedcluster.txt"

nPatients in clinical file=185, in cluster file=185, common to both=185
[1]  10 185
[1] "CN_CNMF"
[1] 3
 1  2  3 
74 33 77 
 1  2  3 
74 33 77 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3  4  5  6  7 
37 42  2 41 37 17  9 
 1  2  4  5  6  7 
37 42 41 37 17  9 
[1] "RPPA_CNMF"
[1] 3
 1  2  3  4  5 
26 28 30 34  8 
 1  2  3  4  5 
26 28 30 34  8 
[1] "RPPA_CHIERARCHICAL"
[1] 3
 1  2  3  4  5 
23 21 22 26 34 
 1  2  3  4  5 
23 21 22 26 34 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2  3  4  5  6 
74 14 42 29  9 16 
 1  2  3  4  5  6 
74 14 42 29  9 16 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
 1  2  3 
68 20 96 
 1  2  3 
68 20 96 
[1] "MIRSEQ_CNMF"
[1] 3
 1  2  3  4  5  6 
71 15 10 18 28 42 
 1  2  3  4  5  6 
71 15 10 18 28 42 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
 1  2  3  4 
63 26 62 33 
 1  2  3  4 
63 26 62 33 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
 1  2  3  4 
65 67 35 12 
 1  2  3  4 
65 67 35 12 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
 1  2  3 
56 29 94 
 1  2  3 
56 29 94 
[1] "data2feature, selection=ALL"
 [1] "YEARS_TO_BIRTH"                      
 [2] "VITAL_STATUS"                        
 [3] "DAYS_TO_DEATH"                       
 [4] "DAYS_TO_LAST_FOLLOWUP"               
 [5] "TUMOR_TISSUE_SITE"                   
 [6] "PATHOLOGIC_STAGE"                    
 [7] "PATHOLOGY_T_STAGE"                   
 [8] "PATHOLOGY_N_STAGE"                   
 [9] "PATHOLOGY_M_STAGE"                   
[10] "GENDER"                              
[11] "DATE_OF_INITIAL_PATHOLOGIC_DIAGNOSIS"
[12] "RADIATION_THERAPY"                   
[13] "KARNOFSKY_PERFORMANCE_SCORE"         
[14] "HISTOLOGICAL_TYPE"                   
[15] "NUMBER_PACK_YEARS_SMOKED"            
[16] "RESIDUAL_TUMOR"                      
[17] "NUMBER_OF_LYMPH_NODES"               
[18] "RACE"                                
[19] "ETHNICITY"                           

Input Data has 19 rows and 185 columns.

[1] "Last Follow UP"
Variable 1:'YEARS_TO_BIRTH':	nDistinctValues=46,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 2:'VITAL_STATUS':	nDistinctValues=2,	numeric=TRUE,	binary=TRUE,	exclude=FALSE.
Variable 3:'DAYS_TO_DEATH':	nDistinctValues=75,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
[1] "exclude grep('DAYS_?TO', vnms) to deal with survival parameters seperately"
Variable 4:'DAYS_TO_LAST_FOLLOWUP':	nDistinctValues=96,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
[1] "exclude grep('FOLLOWUP', vnms) to deal with survival parameters seperately"
Variable 5:'TUMOR_TISSUE_SITE':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "TUMOR_TISSUE_SITE is excluded in the analysis because there is no more than two cases of (unique non-NA values)"
Variable 6:'PATHOLOGIC_STAGE':	nDistinctValues=12,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 7:'PATHOLOGY_T_STAGE':	nDistinctValues=6,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 8:'PATHOLOGY_N_STAGE':	nDistinctValues=5,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 9:'PATHOLOGY_M_STAGE':	nDistinctValues=4,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 10:'GENDER':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 11:'DATE_OF_INITIAL_PATHOLOGIC_DIAGNOSIS':	nDistinctValues=15,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
[1] "exclude grep('DATE', vnms) to deal with survival parameters seperately"
Variable 12:'RADIATION_THERAPY':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 13:'KARNOFSKY_PERFORMANCE_SCORE':	nDistinctValues=8,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 14:'HISTOLOGICAL_TYPE':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 15:'NUMBER_PACK_YEARS_SMOKED':	nDistinctValues=46,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 16:'RESIDUAL_TUMOR':	nDistinctValues=4,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 17:'NUMBER_OF_LYMPH_NODES':	nDistinctValues=14,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 18:'RACE':	nDistinctValues=3,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 19:'ETHNICITY':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
[1] "## **** detect survival parameters (defined in index such as ind_OS, ind_MFS, ind_RFS, ind_RFS, ind_BCR and ind_d2ssd) *** ##"
[1] "detected survival parameters using [ind_OS, overall_survival]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survival parameters using [ind_OS, curated_overall_survival]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survival parameters using [ind_TCGAOS]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survivial parameters using [ind_MFS]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survival parameters using [ind_RFS]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survival parameters using [ind_BCR]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survival parameters using [ind_Progression]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survival parameters using [index_additional_survival_time]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "detected survival parameters using condition: [is.null(surv.mat)&&(selection=='SURV')]"
[1] "survival parameters accumulated so far"
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "************ conversion from categorical data to rank data ********** "
[1] "PATHOLOGY_T_STAGE is converted to numeric rank data using modified categoies"
[1] "PATHOLOGY_N_STAGE is converted to numeric rank data using modified categoies"
[1] "PATHOLOGY_M_STAGE is converted to rank data using modified categoies"
[1] "****** SUMMARY ***** "
Output Data has 185 columns, 1 survival variables, and 14 non-survival variables.
[1] "* survival variables: "
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "* non-survival variables: "
 [1] "YEARS_TO_BIRTH"              "PATHOLOGIC_STAGE"           
 [3] "PATHOLOGY_T_STAGE"           "PATHOLOGY_N_STAGE"          
 [5] "PATHOLOGY_M_STAGE"           "GENDER"                     
 [7] "RADIATION_THERAPY"           "KARNOFSKY_PERFORMANCE_SCORE"
 [9] "HISTOLOGICAL_TYPE"           "NUMBER_PACK_YEARS_SMOKED"   
[11] "RESIDUAL_TUMOR"              "NUMBER_OF_LYMPH_NODES"      
[13] "RACE"                        "ETHNICITY"                  
YEARS_TO_BIRTH, nv=46, binary=FALSE, numeric=TRUE
PATHOLOGIC_STAGE, nv=12, binary=FALSE, numeric=FALSE
PATHOLOGY_T_STAGE, nv=5, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.T',vnm)"
vv
T0 T1 T2 T3 T4 
 1 31 43 88  5 
[1] "table(vv)"
vv
T0+T1    T2    T3    T4 
   32    43    88     5 
$ClinVariableName
[1] "PATHOLOGY_T_STAGE"

$Table
vv
T0 T1 T2 T3 T4 
 1 31 43 88  5 

$nClasses
[1] 4

$ClinVariableType
[1] "multiclass(4)"


T0+T1    T2    T3    T4 
   32    43    88     5 
PATHOLOGY_N_STAGE, nv=4, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.N',vnm)"
vv
N0 N1 N2 N3 
77 69 12  8 
[1] "table(vv)"
vv
N0 N1 N2 N3 
77 69 12  8 
$ClinVariableName
[1] "PATHOLOGY_N_STAGE"

$Table
vv
N0 N1 N2 N3 
77 69 12  8 

$nClasses
[1] 4

$ClinVariableType
[1] "multiclass(4)"


N0 N1 N2 N3 
77 69 12  8 
PATHOLOGY_M_STAGE, nv=2, binary=FALSE, numeric=TRUE
GENDER, nv=2, binary=FALSE, numeric=FALSE
RADIATION_THERAPY, nv=2, binary=FALSE, numeric=FALSE
KARNOFSKY_PERFORMANCE_SCORE, nv=8, binary=FALSE, numeric=TRUE
HISTOLOGICAL_TYPE, nv=2, binary=FALSE, numeric=FALSE
NUMBER_PACK_YEARS_SMOKED, nv=46, binary=FALSE, numeric=TRUE
RESIDUAL_TUMOR, nv=4, binary=FALSE, numeric=FALSE
NUMBER_OF_LYMPH_NODES, nv=14, binary=FALSE, numeric=TRUE
RACE, nv=3, binary=FALSE, numeric=FALSE
ETHNICITY, nv=2, binary=FALSE, numeric=FALSE

Clustering(1) Variable = CN_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 35 39
  subtype2 24  9
  subtype3 49 28
subtype1 subtype2 subtype3 
      74       33       77 
subtype1 subtype2 subtype3 
      39        9       28 
$subtype1
TCGA-JY-A6FB TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A88Y 
       60.39        18.28         8.94        24.00         4.70         0.36 
TCGA-L5-A8NG TCGA-L5-A8NT TCGA-S8-A6BV TCGA-2H-A9GF TCGA-2H-A9GH TCGA-2H-A9GI 
       35.97        27.12        20.02        25.78        31.27        14.30 
TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO 
       58.55         7.63         5.92        13.94         8.94        16.24 
TCGA-2H-A9GQ TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FH 
        4.21        32.45         7.69         3.88       122.10        47.38 
TCGA-JY-A93C TCGA-JY-A93D TCGA-JY-A93E TCGA-L5-A4OF TCGA-L5-A4OH TCGA-L5-A4ON 
       23.18        31.56        25.22        26.33        32.61        18.35 
TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW 
        7.17         1.38         3.16         4.90        29.00         7.13 
TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH 
        7.43         2.60         3.75        55.50         2.66        12.92 
TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NW TCGA-L7-A6VZ 
       16.47        13.22         8.71        13.41        46.09        10.36 
TCGA-LN-A49L TCGA-LN-A49U TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DN TCGA-R6-A6DQ 
       10.45        15.35        33.11         7.82         8.02         7.59 
TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 
        5.06        16.31        38.40         6.35        53.95         9.30 
TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WC TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-A7RE 
       15.78         2.89         2.30         7.00         5.29        16.44 
TCGA-V5-AASW TCGA-VR-A8EP TCGA-VR-A8EQ TCGA-VR-A8Q7 TCGA-VR-AA4D TCGA-X8-AAAR 
        9.27        27.09        22.82        52.27        46.19        18.21 
TCGA-Z6-AAPN TCGA-ZR-A9CJ 
        2.66        19.73 

$subtype2
TCGA-IC-A6RF TCGA-JY-A938 TCGA-L5-A4OI TCGA-L5-A88T TCGA-IG-A3YA TCGA-IG-A3YC 
       15.68        34.85        19.99        22.82        20.78        20.12 
TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A6FD TCGA-JY-A6FG TCGA-JY-A939 TCGA-JY-A93F 
        9.30        14.86        68.02        41.52        21.70        24.03 
TCGA-KH-A6WC TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A4OJ TCGA-L5-A4OO TCGA-L5-A4OS 
        6.28         3.16        30.25        21.01         3.32        58.59 
TCGA-L5-A88W TCGA-L5-A893 TCGA-L5-A8NI TCGA-L5-A8NK TCGA-L5-A8NM TCGA-L5-A8NN 
       25.12         3.02        13.48        13.55         7.76         5.49 
TCGA-L5-A8NQ TCGA-L5-A8NU TCGA-LN-A49X TCGA-LN-A9FP TCGA-R6-A6L6 TCGA-V5-AASV 
       21.37        83.24        12.62        12.03         7.04        15.35 
TCGA-V5-AASX TCGA-VR-A8ET TCGA-Z6-A8JD 
        8.98         1.55         3.42 

$subtype3
TCGA-L5-A43J TCGA-Q9-A6FU TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YB 
        4.31         5.16        33.27        35.21         0.85         2.63 
TCGA-IG-A4P3 TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 
       18.64         0.53        17.03         0.79        23.41        12.82 
TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FA TCGA-JY-A6FE 
        9.96         4.67        14.50        12.16        44.75         3.68 
TCGA-L5-A43H TCGA-L5-A4OM TCGA-L5-A88S TCGA-L5-A88Z TCGA-L5-A8NV TCGA-L7-A56G 
        0.30        47.93        15.48         7.40        52.57        10.85 
TCGA-LN-A49K TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R 
        5.92        12.66        12.43        13.41        12.33        13.38 
TCGA-LN-A49S TCGA-LN-A49V TCGA-LN-A49W TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4A2 
       13.15        12.59        13.25        12.46        12.59        12.49 
TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
       12.76        12.59        22.39        12.85        15.52        11.54 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV 
       12.33        13.22         4.47        12.33        25.25        10.52 
TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A8I0 
       12.00        12.23        12.03        13.18        12.33        13.38 
TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FQ TCGA-LN-A9FR TCGA-R6-A8WG TCGA-S8-A6BW 
       13.18         0.13        12.85        12.26        12.69        20.38 
TCGA-V5-A7RC TCGA-VR-A8EO TCGA-VR-A8ER TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8EX 
        3.42        25.81        12.43        18.31         8.12        28.11 
TCGA-VR-A8EY TCGA-VR-A8EZ TCGA-VR-AA4G TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I 
       33.70        18.18        18.05        11.24         9.17        15.91 
TCGA-XP-A8T6 TCGA-XP-A8T7 TCGA-XP-A8T8 TCGA-Z6-A8JE TCGA-Z6-A9VB 
       25.08        41.23        14.37         2.10         1.32 

subtype1 subtype2 subtype3 
    0.36     1.55     0.13 
subtype1 subtype2 subtype3 
  122.10    83.24    52.57 
subtype1 subtype2 subtype3 
   14.12    15.35    12.59 
[1] "0.4 - 122.1 (14.1)" "1.6 - 83.2 (15.3)"  "0.1 - 52.6 (12.6)" 
D1V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       5        2        2        0         6        13        12
  subtype2       3        2        1        0         9         7         3
  subtype3       0        1        3        1        32        11        10
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          5          5          3        2         3
  subtype2          3          0          2        0         0
  subtype3          6          4          2        3         1
D1V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           5        3        0
  STAGE IA          2        2        1
  STAGE IB          2        1        3
  STAGE II          0        0        1
  STAGE IIA         6        9       32
  STAGE IIB        13        7       11
  STAGE III        12        3       10
  STAGE IIIA        5        3        6
  STAGE IIIB        5        0        4
  STAGE IIIC        3        2        2
  STAGE IV          2        0        3
  STAGE IVA         3        0        1
[1] 12  3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    20  8 35  0
  subtype2     6  8 14  2
  subtype3     6 27 38  3
D1V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       20        6        6
  T2           8        8       27
  T3          35       14       38
  T4           0        2        3
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1 19 34  7  3
  subtype2 19  8  0  2
  subtype3 39 26  5  3
D1V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       19       19       39
  N1       34        8       26
  N2        7        0        5
  N3        3        2        3
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V6, binary
          cls
clus        0  1
  subtype1 43  5
  subtype2 26  0
  subtype3 66  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   43    5
  subtype2   26    0
  subtype3   66    4
   clus
vv  subtype1 subtype2 subtype3
  0       43       26       66
  1        5        0        4
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V7, binary
          cls
clus        0  1
  subtype1  7 67
  subtype2 10 23
  subtype3 10 67
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7   67
  subtype2   10   23
  subtype3   10   67
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        7       10       10
  MALE         67       23       67
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V8, binary
          cls
clus        0  1
  subtype1 54 11
  subtype2 23  6
  subtype3 46 26
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   54   11
  subtype2   23    6
  subtype3   46   26
     clus
vv    subtype1 subtype2 subtype3
  NO        54       23       46
  YES       11        6       26
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V9, continuous
D1V10, binary
          cls
clus        0  1
  subtype1 69  5
  subtype2 17 16
  subtype3  2 75
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   69    5
  subtype2   17   16
  subtype3    2   75
                                   clus
vv                                  subtype1 subtype2 subtype3
  ESOPHAGUS ADENOCARCINOMA, NOS           69       17        2
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        5       16       75
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 49  7  0  3
  subtype2 27  2  0  0
  subtype3 61  3  2  4
D1V12, multiclass
    clus
vv   subtype1 subtype2 subtype3
  R0       49       27       61
  R1        7        2        3
  R2        0        0        2
  RX        3        0        4
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     3                         0    55
  subtype2     3                         1    29
  subtype3    40                         4    30
D1V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            3        3       40
  BLACK OR AFRICAN AMERICAN        0        1        4
  WHITE                           55       29       30
[1] 3 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V15, binary
          cls
clus        0  1
  subtype1  2 23
  subtype2  0 12
  subtype3  4 53
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   23
  subtype2    0   12
  subtype3    4   53
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            2        0        4
  NOT HISPANIC OR LATINO       23       12       53
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(2) Variable = METHLYATION_CNMF
D2V1, survival
          sevent
clus2       0  1
  subtype1 11 26
  subtype2 26 16
  subtype4 26 15
  subtype5 25 12
  subtype6 11  6
  subtype7  7  2
subtype1 subtype2 subtype4 subtype5 subtype6 subtype7 
      37       42       41       37       17        9 
subtype1 subtype2 subtype4 subtype5 subtype6 subtype7 
      26       16       15       12        6        2 
$subtype1
TCGA-L5-A43I TCGA-S8-A6BV TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GJ 
       18.28        20.02        25.78        20.05        31.27        58.55 
TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GQ TCGA-IC-A6RE TCGA-IG-A4QS 
       13.94         8.94        16.24         4.21         7.69         3.88 
TCGA-JY-A6FH TCGA-L5-A4OF TCGA-L5-A4OH TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR 
       47.38        26.33        32.61         7.17         1.38         3.16 
TCGA-L5-A4OT TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH TCGA-L5-A8NI 
        4.90         3.75        55.50         2.66        12.92        13.48 
TCGA-L5-A8NN TCGA-R6-A6KZ TCGA-R6-A6L6 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 
        5.49         5.06         7.04        38.40         6.35        53.95 
TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WG TCGA-V5-A7RE TCGA-VR-AA4D 
        9.30        15.78         2.89        12.69        16.44        46.19 
TCGA-ZR-A9CJ 
       19.73 

$subtype2
TCGA-JY-A6FB TCGA-JY-A938 TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A4OI TCGA-L5-A88Y 
       60.39        34.85        24.00         4.70        19.99         0.36 
TCGA-L5-A8NG TCGA-L5-A8NT TCGA-2H-A9GI TCGA-2H-A9GK TCGA-2H-A9GL TCGA-2H-A9GR 
       35.97        27.12        14.30         7.63         5.92        32.45 
TCGA-JY-A6F8 TCGA-JY-A93C TCGA-JY-A93E TCGA-L5-A43E TCGA-L5-A4OJ TCGA-L5-A4ON 
      122.10        23.18        25.22        30.25        21.01        18.35 
TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A893 TCGA-L5-A8NJ 
       29.00         7.13         7.43         2.60         3.02        16.47 
TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NV TCGA-L5-A8NW 
       13.22         7.76         8.71        13.41        52.57        46.09 
TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A8WC 
       10.36        33.11         7.82         8.02         7.59         2.30 
TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-AASW TCGA-V5-AASX TCGA-VR-A8EQ TCGA-X8-AAAR 
        7.00         5.29         9.27         8.98        22.82        18.21 

$subtype4
TCGA-Q9-A6FU TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A4P3 TCGA-IG-A50L TCGA-IG-A625 
        5.16        33.27        35.21        18.64         0.53        12.82 
TCGA-IG-A8O2 TCGA-IG-A97H TCGA-JY-A6FA TCGA-L5-A43H TCGA-L5-A4OM TCGA-L5-A88Z 
        4.67        14.50        44.75         0.30        47.93         7.40 
TCGA-LN-A49K TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49Y TCGA-LN-A4A2 
        5.92        13.38        13.15        15.35        12.46        12.49 
TCGA-LN-A4A4 TCGA-LN-A4A8 TCGA-LN-A4MQ TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 
       12.59        15.52        12.33         4.47        12.33        25.25 
TCGA-LN-A7HW TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-LN-A9FQ 
       12.00        13.18        12.33        13.38        13.18        12.85 
TCGA-S8-A6BW TCGA-V5-A7RC TCGA-VR-A8EO TCGA-VR-A8EP TCGA-VR-A8ER TCGA-VR-A8EW 
       20.38         3.42        25.81        27.09        12.43         8.12 
TCGA-VR-A8EX TCGA-VR-A8EZ TCGA-XP-A8T6 TCGA-XP-A8T8 TCGA-Z6-A9VB 
       28.11        18.18        25.08        14.37         1.32 

$subtype5
TCGA-L5-A43J TCGA-IG-A3Y9 TCGA-IG-A3YC TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A6QS 
        4.31         0.85        20.12        17.03         0.79         9.96 
TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-JY-A93F TCGA-L5-A88S TCGA-L5-A88W 
       68.02         3.68        41.52        24.03        15.48        25.12 
TCGA-L5-A8NK TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49W 
       13.55        10.45        12.66        12.43        13.41        13.25 
TCGA-LN-A4A1 TCGA-LN-A4A3 TCGA-LN-A4A6 TCGA-LN-A4A9 TCGA-LN-A4MR TCGA-LN-A7HV 
       12.59        12.76        12.85        11.54        13.22        10.52 
TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A9FO TCGA-LN-A9FR TCGA-VR-A8EU TCGA-VR-A8EY 
       12.23        12.03         0.13        12.26        18.31        33.70 
TCGA-VR-A8Q7 TCGA-VR-AA4G TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I TCGA-XP-A8T7 
       52.27        18.05        11.24         9.17        15.91        41.23 
TCGA-Z6-A8JE 
        2.10 

$subtype6
TCGA-IG-A3YA TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A939 TCGA-JY-A93D TCGA-KH-A6WC 
       20.78         9.30        14.86        21.70        31.56         6.28 
TCGA-L5-A43C TCGA-L5-A4OO TCGA-L5-A4OS TCGA-L5-A8NQ TCGA-L5-A8NU TCGA-LN-A49X 
        3.16         3.32        58.59        21.37        83.24        12.62 
TCGA-LN-A4A5 TCGA-LN-A9FP TCGA-VR-A8ET TCGA-Z6-A8JD TCGA-Z6-AAPN 
       22.39        12.03         1.55         3.42         2.66 

$subtype7
TCGA-L5-A43M TCGA-L5-A88T TCGA-IG-A3YB TCGA-IG-A5S3 TCGA-IG-A97I TCGA-L7-A56G 
        8.94        22.82         2.63        23.41        12.16        10.85 
TCGA-LN-A49P TCGA-LN-A49V TCGA-R6-A6L4 
       12.33        12.59        16.31 

subtype1 subtype2 subtype4 subtype5 subtype6 subtype7 
    1.38     0.36     0.30     0.13     1.55     2.63 
subtype1 subtype2 subtype4 subtype5 subtype6 subtype7 
   58.55   122.10    47.93    68.02    83.24    23.41 
subtype1 subtype2 subtype4 subtype5 subtype6 subtype7 
  13.480   13.855   13.150   12.760   12.620   12.330 
[1] "1.4 - 58.5 (13.5)"  "0.4 - 122.1 (13.9)" "0.3 - 47.9 (13.2)" 
[4] "0.1 - 68.0 (12.8)"  "1.6 - 83.2 (12.6)"  "2.6 - 23.4 (12.3)" 
D2V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       2        2        1        0         0         7         6
  subtype2       6        0        1        0         4         8         9
  subtype4       0        1        1        0        18         5         5
  subtype5       0        0        3        1        14         5         6
  subtype6       0        1        0        0         8         3         0
  subtype7       0        0        0        0         3         2         0
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          3          1          1        2         3
  subtype2          1          3          2        0         0
  subtype4          2          5          1        1         1
  subtype5          5          0          1        2         0
  subtype6          2          0          2        0         0
  subtype7          1          0          0        0         0
D2V3, multiclass
            clus
vv           subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  STAGE I           2        6        0        0        0        0
  STAGE IA          2        0        1        0        1        0
  STAGE IB          1        1        1        3        0        0
  STAGE II          0        0        0        1        0        0
  STAGE IIA         0        4       18       14        8        3
  STAGE IIB         7        8        5        5        3        2
  STAGE III         6        9        5        6        0        0
  STAGE IIIA        3        1        2        5        2        1
  STAGE IIIB        1        3        5        0        0        0
  STAGE IIIC        1        2        1        1        2        0
  STAGE IV          2        0        1        2        0        0
  STAGE IVA         3        0        1        0        0        0
[1] 12  6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    12  3 14  0
  subtype2    11  4 22  0
  subtype4     4 13 22  1
  subtype5     2 14 19  2
  subtype6     2  7  5  2
  subtype7     0  2  5  0
D2V4, multiclass
       clus
vv      subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  T0+T1       12       11        4        2        2        0
  T2           3        4       13       14        7        2
  T3          14       22       22       19        5        5
  T4           0        0        1        2        2        0
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1  7 19  2  1
  subtype2 14 18  3  2
  subtype4 18 15  5  1
  subtype5 21 13  1  2
  subtype6 11  2  0  2
  subtype7  4  2  1  0
D2V5, multiclass
    clus
vv   subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  N0        7       14       18       21       11        4
  N1       19       18       15       13        2        2
  N2        2        3        5        1        0        1
  N3        1        2        1        2        2        0
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V6, binary
          cls
clus        0  1
  subtype1 17  5
  subtype2 29  0
  subtype4 36  2
  subtype5 32  2
  subtype6 15  0
  subtype7  6  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   17    5
  subtype2   29    0
  subtype4   36    2
  subtype5   32    2
  subtype6   15    0
  subtype7    6    0
   clus
vv  subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  0       17       29       36       32       15        6
  1        5        0        2        2        0        0
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V7, binary
          cls
clus        0  1
  subtype1  1 36
  subtype2  8 34
  subtype4  5 36
  subtype5  7 30
  subtype6  3 14
  subtype7  2  7
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    1   36
  subtype2    8   34
  subtype4    5   36
  subtype5    7   30
  subtype6    3   14
  subtype7    2    7
        clus
vv       subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  FEMALE        1        8        5        7        3        2
  MALE         36       34       36       30       14        7
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V8, binary
          cls
clus        0  1
  subtype1 31  3
  subtype2 30  5
  subtype4 24 13
  subtype5 24 11
  subtype6 10  5
  subtype7  4  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   31    3
  subtype2   30    5
  subtype4   24   13
  subtype5   24   11
  subtype6   10    5
  subtype7    4    5
     clus
vv    subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  NO        31       30       24       24       10        4
  YES        3        5       13       11        5        5
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V9, continuous
[1] "Remove cluster labels:" "subtype1"              
clus
subtype1 subtype2 subtype4 subtype5 subtype6 subtype7 
       2        4       25       25        7        4 
 [1] "subtype4" "subtype4" "subtype5" "subtype6" "subtype7" "subtype5"
 [7] "subtype5" "subtype7" "subtype6" "subtype6" "subtype4" "subtype5"
[13] "subtype5" "subtype5" "subtype5" "subtype7" "subtype4" "subtype4"
[19] "subtype4" "subtype7" "subtype5" "subtype6" "subtype4" "subtype5"
[25] "subtype4" "subtype5" "subtype4" "subtype6" "subtype5" "subtype4"
[31] "subtype5" "subtype4" "subtype5" "subtype4" "subtype4" "subtype4"
[37] "subtype5" "subtype4" "subtype5" "subtype5" "subtype4" "subtype2"
[43] "subtype4" "subtype2" "subtype2" "subtype4" "subtype4" "subtype2"
[49] "subtype4" "subtype6" "subtype5" "subtype4" "subtype4" "subtype5"
[55] "subtype4" "subtype5" "subtype5" "subtype5" "subtype5" "subtype5"
[61] "subtype4" "subtype5" "subtype4" "subtype6" "subtype5"
D2V10, binary
          cls
clus        0  1
  subtype1 37  0
  subtype2 42  0
  subtype4  0 41
  subtype5  0 37
  subtype6  7 10
  subtype7  3  6
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   37    0
  subtype2   42    0
  subtype4    0   41
  subtype5    0   37
  subtype6    7   10
  subtype7    3    6
                                   clus
vv                                  subtype1 subtype2 subtype4 subtype5
  ESOPHAGUS ADENOCARCINOMA, NOS           37       42        0        0
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0        0       41       37
                                   clus
vv                                  subtype6 subtype7
  ESOPHAGUS ADENOCARCINOMA, NOS            7        3
  ESOPHAGUS SQUAMOUS CELL CARCINOMA       10        6
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 21  5  0  0
  subtype2 31  3  0  2
  subtype4 34  3  1  1
  subtype5 29  2  1  3
  subtype6 15  0  0  0
  subtype7  5  0  0  1
D2V12, multiclass
    clus
vv   subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  R0       21       31       34       29       15        5
  R1        5        3        3        2        0        0
  R2        0        0        1        1        0        0
  RX        0        2        1        3        0        1
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    29
  subtype2     1                         0    33
  subtype4    24                         3    12
  subtype5    16                         0    20
  subtype6     3                         0    14
  subtype7     2                         1     5
D2V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype4 subtype5 subtype6
  ASIAN                            0        1       24       16        3
  BLACK OR AFRICAN AMERICAN        0        0        3        0        0
  WHITE                           29       33       12       20       14
                           clus
vv                          subtype7
  ASIAN                            2
  BLACK OR AFRICAN AMERICAN        1
  WHITE                            5
[1] 3 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V15, binary
          cls
clus        0  1
  subtype1  2 12
  subtype2  1  9
  subtype4  2 29
  subtype5  1 20
  subtype6  0  9
  subtype7  0  7
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   12
  subtype2    1    9
  subtype4    2   29
  subtype5    1   20
  subtype6    0    9
  subtype7    0    7
                        clus
vv                       subtype1 subtype2 subtype4 subtype5 subtype6 subtype7
  HISPANIC OR LATINO            2        1        2        1        0        0
  NOT HISPANIC OR LATINO       12        9       29       20        9        7
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(3) Variable = RPPA_CNMF
D3V1, survival
          sevent
clus2       0  1
  subtype1 13 13
  subtype2 21  7
  subtype3 19 11
  subtype4 25  9
  subtype5  4  4
subtype1 subtype2 subtype3 subtype4 subtype5 
      26       28       30       34        8 
subtype1 subtype2 subtype3 subtype4 subtype5 
      13        7       11        9        4 
$subtype1
TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE TCGA-2H-A9GF TCGA-2H-A9GR TCGA-IC-A6RE 
       18.28         8.94        24.00        25.78        32.45         7.69 
TCGA-IG-A3YB TCGA-IG-A4QS TCGA-JY-A939 TCGA-L5-A43E TCGA-L5-A4OH TCGA-L5-A4OJ 
        2.63         3.88        21.70        30.25        32.61        21.01 
TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OR TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A8NF 
       18.35         7.17         3.16         7.13         7.43         2.66 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-LN-A49L 
       13.48        16.47        13.22        46.09        10.36        10.45 
TCGA-LN-A49Y TCGA-Z6-A8JE 
       12.46         2.10 

$subtype2
TCGA-JY-A6FB TCGA-L5-A4OG TCGA-L5-A4OI TCGA-2H-A9GI TCGA-IG-A3YC TCGA-IG-A50L 
       60.39         4.70        19.99        14.30        20.12         0.53 
TCGA-IG-A6QS TCGA-IG-A97H TCGA-JY-A6F8 TCGA-JY-A93F TCGA-L5-A4OQ TCGA-L5-A4OS 
        9.96        14.50       122.10        24.03         1.38        58.59 
TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NQ TCGA-L7-A56G TCGA-LN-A4A2 TCGA-LN-A4A6 
        3.75        55.50        21.37        10.85        12.49        12.85 
TCGA-LN-A4A8 TCGA-LN-A8I1 TCGA-LN-A9FP TCGA-M9-A5M8 TCGA-RE-A7BO TCGA-VR-A8EO 
       15.52        13.18        12.03        33.11         7.00        25.81 
TCGA-VR-A8EQ TCGA-Z6-A8JD TCGA-Z6-A9VB TCGA-Z6-AAPN 
       22.82         3.42         1.32         2.66 

$subtype3
TCGA-IC-A6RF TCGA-L5-A8NT TCGA-2H-A9GL TCGA-IG-A3YA TCGA-IG-A4P3 TCGA-IG-A4QT 
       15.68        27.12         5.92        20.78        18.64         9.30 
TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A8O2 TCGA-JY-A93E 
       17.03         0.79        23.41        12.82         4.67        25.22 
TCGA-L5-A43C TCGA-L5-A43H TCGA-L5-A4OF TCGA-L5-A4OT TCGA-L5-A8NS TCGA-L5-A8NV 
        3.16         0.30        26.33         4.90        13.41        52.57 
TCGA-LN-A49N TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A3 TCGA-LN-A4A9 TCGA-LN-A4MQ 
       12.43        13.25        12.62        12.76        11.54        12.33 
TCGA-LN-A7HY TCGA-LN-A8I0 TCGA-LN-A9FQ TCGA-Q9-A6FW TCGA-VR-AA7B TCGA-X8-AAAR 
       12.03        13.38        12.85         7.82        11.24        18.21 

$subtype4
TCGA-L5-A43J TCGA-Q9-A6FU TCGA-2H-A9GQ TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 
        4.31         5.16         4.21        33.27        35.21         0.85 
TCGA-IG-A97I TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-L5-A8NK 
       12.16        44.75        68.02         3.68        41.52        13.55 
TCGA-LN-A49K TCGA-LN-A49M TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R TCGA-LN-A49U 
        5.92        12.66        13.41        12.33        13.38        15.35 
TCGA-LN-A49V TCGA-LN-A4A1 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4MR TCGA-LN-A5U6 
       12.59        12.59        12.59        22.39        13.22        12.33 
TCGA-LN-A5U7 TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A9FO 
       25.25        12.00        12.23        13.18        12.33         0.13 
TCGA-LN-A9FR TCGA-S8-A6BW TCGA-VR-A8Q7 TCGA-XP-A8T7 
       12.26        20.38        52.27        41.23 

$subtype5
TCGA-S8-A6BV TCGA-L5-A4OU TCGA-L5-A88W TCGA-LN-A49S TCGA-LN-A5U5 TCGA-VR-A8EP 
       20.02        29.00        25.12        13.15         4.47        27.09 
TCGA-VR-AA4D TCGA-XP-A8T6 
       46.19        25.08 

subtype1 subtype2 subtype3 subtype4 subtype5 
    2.10     0.53     0.30     0.13     4.47 
subtype1 subtype2 subtype3 subtype4 subtype5 
   46.09   122.10    52.57    68.02    46.19 
subtype1 subtype2 subtype3 subtype4 subtype5 
  12.840   13.740   12.790   12.625   25.100 
[1] "2.1 - 46.1 (12.8)"  "0.5 - 122.1 (13.7)" "0.3 - 52.6 (12.8)" 
[4] "0.1 - 68.0 (12.6)"  "4.5 - 46.2 (25.1)" 
D3V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       3        2        1        0         3         5         4
  subtype2       3        0        1        1         9         5         2
  subtype3       0        1        1        0         6         7         6
  subtype4       0        0        1        0        21         4         5
  subtype5       0        0        0        0         3         2         0
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          3          2          1        0         1
  subtype2          4          0          1        0         0
  subtype3          2          3          0        2         0
  subtype4          2          1          0        0         0
  subtype5          1          1          0        1         0
D3V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5
  STAGE I           3        3        0        0        0
  STAGE IA          2        0        1        0        0
  STAGE IB          1        1        1        1        0
  STAGE II          0        1        0        0        0
  STAGE IIA         3        9        6       21        3
  STAGE IIB         5        5        7        4        2
  STAGE III         4        2        6        5        0
  STAGE IIIA        3        4        2        2        1
  STAGE IIIB        2        0        3        1        1
  STAGE IIIC        1        1        0        0        0
  STAGE IV          0        0        2        0        1
  STAGE IVA         1        0        0        0        0
[1] 12  5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1     9  4 13  0
  subtype2     4 10 13  0
  subtype3     4  4 20  1
  subtype4     0 16 17  1
  subtype5     1  1  6  0
D3V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4 subtype5
  T0+T1        9        4        4        0        1
  T2           4       10        4       16        1
  T3          13       13       20       17        6
  T4           0        0        1        1        0
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1  9 13  3  1
  subtype2 14 10  1  1
  subtype3 12 13  3  1
  subtype4 24  9  1  0
  subtype5  3  4  1  0
D3V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5
  N0        9       14       12       24        3
  N1       13       10       13        9        4
  N2        3        1        3        1        1
  N3        1        1        1        0        0
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V6, binary
          cls
clus        0  1
  subtype1 18  1
  subtype2 25  0
  subtype3 25  2
  subtype4 32  0
  subtype5  5  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   18    1
  subtype2   25    0
  subtype3   25    2
  subtype4   32    0
  subtype5    5    1
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5
  0       18       25       25       32        5
  1        1        0        2        0        1
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V7, binary
          cls
clus        0  1
  subtype1  4 22
  subtype2  6 22
  subtype3  3 27
  subtype4  5 29
  subtype5  0  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    4   22
  subtype2    6   22
  subtype3    3   27
  subtype4    5   29
  subtype5    0    8
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5
  FEMALE        4        6        3        5        0
  MALE         22       22       27       29        8
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V8, binary
          cls
clus        0  1
  subtype1 19  4
  subtype2 19  6
  subtype3 21  7
  subtype4 20 12
  subtype5  5  3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   19    4
  subtype2   19    6
  subtype3   21    7
  subtype4   20   12
  subtype5    5    3
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5
  NO        19       19       21       20        5
  YES        4        6        7       12        3
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V9, continuous
D3V10, binary
          cls
clus        0  1
  subtype1 22  4
  subtype2 12 16
  subtype3 10 20
  subtype4  1 33
  subtype5  3  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   22    4
  subtype2   12   16
  subtype3   10   20
  subtype4    1   33
  subtype5    3    5
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA, NOS           22       12       10        1
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        4       16       20       33
                                   clus
vv                                  subtype5
  ESOPHAGUS ADENOCARCINOMA, NOS            3
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        5
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 20  3  0  3
  subtype2 27  0  0  0
  subtype3 20  4  0  2
  subtype4 29  2  0  2
  subtype5  5  1  1  0
D3V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5
  R0       20       27       20       29        5
  R1        3        0        4        2        1
  R2        0        0        0        0        1
  RX        3        0        2        2        0
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     2                         0    20
  subtype2     7                         1    18
  subtype3    11                         0    18
  subtype4    21                         0    12
  subtype5     2                         1     5
D3V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            2        7       11       21        2
  BLACK OR AFRICAN AMERICAN        0        1        0        0        1
  WHITE                           20       18       18       12        5
[1] 3 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V15, binary
          cls
clus        0  1
  subtype1  0  7
  subtype2  0 14
  subtype3  0 19
  subtype4  1 25
  subtype5  1  3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    0    7
  subtype2    0   14
  subtype3    0   19
  subtype4    1   25
  subtype5    1    3
                        clus
vv                       subtype1 subtype2 subtype3 subtype4 subtype5
  HISPANIC OR LATINO            0        0        0        1        1
  NOT HISPANIC OR LATINO        7       14       19       25        3
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(4) Variable = RPPA_CHIERARCHICAL
D4V1, survival
          sevent
clus2       0  1
  subtype1 12 11
  subtype2 15  6
  subtype3 12 10
  subtype4 19  7
  subtype5 24 10
subtype1 subtype2 subtype3 subtype4 subtype5 
      23       21       22       26       34 
subtype1 subtype2 subtype3 subtype4 subtype5 
      11        6       10        7       10 
$subtype1
TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OI TCGA-S8-A6BV TCGA-2H-A9GF TCGA-2H-A9GR 
        8.94        24.00        19.99        20.02        25.78        32.45 
TCGA-IC-A6RE TCGA-IG-A4QS TCGA-JY-A939 TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A4OH 
        7.69         3.88        21.70         3.16        30.25        32.61 
TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OW 
       21.01        18.35         7.17         1.38         3.16         7.13 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-VR-AA4D 
       13.48        16.47        46.09        10.36        46.19 

$subtype2
TCGA-JY-A6FB TCGA-L5-A4OG TCGA-2H-A9GI TCGA-IG-A3YC TCGA-IG-A50L TCGA-IG-A6QS 
       60.39         4.70        14.30        20.12         0.53         9.96 
TCGA-JY-A6F8 TCGA-JY-A93F TCGA-L5-A4OS TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NQ 
      122.10        24.03        58.59         3.75        55.50        21.37 
TCGA-L7-A56G TCGA-LN-A4A8 TCGA-LN-A8I1 TCGA-M9-A5M8 TCGA-RE-A7BO TCGA-VR-A8EO 
       10.85        15.52        13.18        33.11         7.00        25.81 
TCGA-VR-A8EQ TCGA-Z6-A8JD TCGA-Z6-AAPN 
       22.82         3.42         2.66 

$subtype3
TCGA-L5-A43I TCGA-L5-A8NT TCGA-2H-A9GL TCGA-IG-A3YA TCGA-IG-A4P3 TCGA-IG-A4QT 
       18.28        27.12         5.92        20.78        18.64         9.30 
TCGA-IG-A625 TCGA-JY-A93E TCGA-L5-A4OF TCGA-L5-A4OT TCGA-L5-A4OX TCGA-L5-A8NF 
       12.82        25.22        26.33         4.90         7.43         2.66 
TCGA-L5-A8NS TCGA-L5-A8NV TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A3 TCGA-LN-A7HY 
       13.41        52.57        13.25        12.62        12.76        12.03 
TCGA-LN-A8I0 TCGA-Q9-A6FW TCGA-VR-AA7B TCGA-X8-AAAR 
       13.38         7.82        11.24        18.21 

$subtype4
TCGA-2H-A9GQ TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A8O2 TCGA-IG-A97H TCGA-JY-A6FE 
        4.21         0.79        23.41         4.67        14.50         3.68 
TCGA-L5-A43H TCGA-L5-A8NL TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R 
        0.30        13.22        12.43        13.41        12.33        13.38 
TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 
       15.35        12.59        12.49        12.59        22.39        12.85 
TCGA-LN-A4A9 TCGA-LN-A7HX TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A9FQ TCGA-LN-A9FR 
       11.54        12.23        13.18        12.33        12.85        12.26 
TCGA-VR-A8Q7 TCGA-Z6-A9VB 
       52.27         1.32 

$subtype5
TCGA-IC-A6RF TCGA-L5-A43J TCGA-Q9-A6FU TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 
       15.68         4.31         5.16        33.27        35.21         0.85 
TCGA-IG-A3YB TCGA-IG-A51D TCGA-IG-A97I TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FG 
        2.63        17.03        12.16        44.75        68.02        41.52 
TCGA-L5-A4OU TCGA-L5-A88W TCGA-L5-A8NK TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M 
       29.00        25.12        13.55         5.92        10.45        12.66 
TCGA-LN-A49S TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 
       13.15        12.46        12.59        12.33        13.22         4.47 
TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HW TCGA-LN-A9FO TCGA-LN-A9FP TCGA-S8-A6BW 
       12.33        25.25        12.00         0.13        12.03        20.38 
TCGA-VR-A8EP TCGA-XP-A8T6 TCGA-XP-A8T7 TCGA-Z6-A8JE 
       27.09        25.08        41.23         2.10 

subtype1 subtype2 subtype3 subtype4 subtype5 
    1.38     0.53     2.66     0.30     0.13 
subtype1 subtype2 subtype3 subtype4 subtype5 
   46.19   122.10    52.57    52.27    68.02 
subtype1 subtype2 subtype3 subtype4 subtype5 
  18.350   15.520   13.035   12.540   12.905 
[1] "1.4 - 46.2 (18.4)"  "0.5 - 122.1 (15.5)" "2.7 - 52.6 (13.0)" 
[4] "0.3 - 52.3 (12.5)"  "0.1 - 68.0 (12.9)" 
D4V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       3        2        1        0         1         5         3
  subtype2       3        0        1        0         6         5         2
  subtype3       0        0        0        0         4         5         4
  subtype4       0        0        1        1        12         3         6
  subtype5       0        1        1        0        19         5         2
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          2          2        0         0
  subtype2          2          0          0        0         0
  subtype3          3          2          0        2         1
  subtype4          2          1          0        0         0
  subtype5          3          2          0        1         0
D4V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5
  STAGE I           3        3        0        0        0
  STAGE IA          2        0        0        0        1
  STAGE IB          1        1        0        1        1
  STAGE II          0        0        0        1        0
  STAGE IIA         1        6        4       12       19
  STAGE IIB         5        5        5        3        5
  STAGE III         3        2        4        6        2
  STAGE IIIA        2        2        3        2        3
  STAGE IIIB        2        0        2        1        2
  STAGE IIIC        2        0        0        0        0
  STAGE IV          0        0        2        0        1
  STAGE IVA         0        0        1        0        0
[1] 12  5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1     9  3 10  0
  subtype2     4  7  9  0
  subtype3     3  3 15  1
  subtype4     0  8 18  0
  subtype5     2 14 17  1
D4V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4 subtype5
  T0+T1        9        4        3        0        2
  T2           3        7        3        8       14
  T3          10        9       15       18       17
  T4           0        0        1        0        1
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1  6 10  4  2
  subtype2 11  9  0  0
  subtype3  8 11  2  1
  subtype4 14 10  1  0
  subtype5 23  9  2  0
D4V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5
  N0        6       11        8       14       23
  N1       10        9       11       10        9
  N2        4        0        2        1        2
  N3        2        0        1        0        0
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V6, binary
          cls
clus        0  1
  subtype1 13  0
  subtype2 20  0
  subtype3 16  3
  subtype4 26  0
  subtype5 30  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   13    0
  subtype2   20    0
  subtype3   16    3
  subtype4   26    0
  subtype5   30    1
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5
  0       13       20       16       26       30
  1        0        0        3        0        1
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V7, binary
          cls
clus        0  1
  subtype1  4 19
  subtype2  5 16
  subtype3  1 21
  subtype4  1 25
  subtype5  7 27
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    4   19
  subtype2    5   16
  subtype3    1   21
  subtype4    1   25
  subtype5    7   27
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5
  FEMALE        4        5        1        1        7
  MALE         19       16       21       25       27
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V8, binary
          cls
clus        0  1
  subtype1 19  2
  subtype2 15  4
  subtype3 13  8
  subtype4 13 10
  subtype5 24  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   19    2
  subtype2   15    4
  subtype3   13    8
  subtype4   13   10
  subtype5   24    8
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5
  NO        19       15       13       13       24
  YES        2        4        8       10        8
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V9, continuous
[1] "Remove cluster labels:" "subtype1"              
clus
subtype1 subtype2 subtype3 subtype4 subtype5 
       1        5        6       15       21 
 [1] "subtype5" "subtype5" "subtype5" "subtype3" "subtype5" "subtype2"
 [7] "subtype5" "subtype4" "subtype5" "subtype5" "subtype5" "subtype4"
[13] "subtype4" "subtype4" "subtype4" "subtype5" "subtype4" "subtype4"
[19] "subtype3" "subtype3" "subtype5" "subtype5" "subtype4" "subtype3"
[25] "subtype4" "subtype4" "subtype4" "subtype2" "subtype4" "subtype5"
[31] "subtype5" "subtype5" "subtype5" "subtype5" "subtype5" "subtype4"
[37] "subtype3" "subtype4" "subtype2" "subtype5" "subtype2" "subtype4"
[43] "subtype3" "subtype5" "subtype5" "subtype2" "subtype5"
D4V10, binary
          cls
clus        0  1
  subtype1 23  0
  subtype2 10 11
  subtype3 12 10
  subtype4  2 24
  subtype5  1 33
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   23    0
  subtype2   10   11
  subtype3   12   10
  subtype4    2   24
  subtype5    1   33
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA, NOS           23       10       12        2
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0       11       10       24
                                   clus
vv                                  subtype5
  ESOPHAGUS ADENOCARCINOMA, NOS            1
  ESOPHAGUS SQUAMOUS CELL CARCINOMA       33
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 18  2  0  2
  subtype2 20  0  0  0
  subtype3 14  4  0  1
  subtype4 24  1  0  0
  subtype5 25  3  1  4
D4V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5
  R0       18       20       14       24       25
  R1        2        0        4        1        3
  R2        0        0        0        0        1
  RX        2        0        1        0        4
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    19
  subtype2     3                         1    15
  subtype3     6                         0    15
  subtype4    18                         0     7
  subtype5    16                         1    17
D4V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            0        3        6       18       16
  BLACK OR AFRICAN AMERICAN        0        1        0        0        1
  WHITE                           19       15       15        7       17
[1] 3 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V15, binary
          cls
clus        0  1
  subtype1  0  4
  subtype2  0  9
  subtype3  0 10
  subtype4  0 21
  subtype5  2 24
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    0    4
  subtype2    0    9
  subtype3    0   10
  subtype4    0   21
  subtype5    2   24
                        clus
vv                       subtype1 subtype2 subtype3 subtype4 subtype5
  HISPANIC OR LATINO            0        0        0        0        2
  NOT HISPANIC OR LATINO        4        9       10       21       24
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(5) Variable = MRNASEQ_CNMF
D5V1, survival
          sevent
clus2       0  1
  subtype1 37 37
  subtype2 10  4
  subtype3 29 13
  subtype4 18 11
  subtype5  5  4
  subtype6  8  8
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
      74       14       42       29        9       16 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
      37        4       13       11        4        8 
$subtype1
TCGA-JY-A6FB TCGA-JY-A938 TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OG 
       60.39        34.85        18.28         8.94        24.00         4.70 
TCGA-L5-A4OI TCGA-L5-A88Y TCGA-L5-A8NG TCGA-S8-A6BV TCGA-2H-A9GF TCGA-2H-A9GG 
       19.99         0.36        35.97        20.02        25.78        20.05 
TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL TCGA-2H-A9GM 
       31.27        14.30        58.55         7.63         5.92        13.94 
TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A4QS TCGA-JY-A6F8 
        8.94        16.24        32.45         7.69         3.88       122.10 
TCGA-JY-A6FH TCGA-JY-A939 TCGA-JY-A93C TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43E 
       47.38        21.70        23.18        25.22         3.16        30.25 
TCGA-L5-A4OF TCGA-L5-A4OH TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP 
       26.33        32.61        21.01        18.35         3.32         7.17 
TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX 
        1.38         3.16         4.90        29.00         7.13         7.43 
TCGA-L5-A88V TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH 
        2.60         3.75         3.02        55.50         2.66        12.92 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NR TCGA-L5-A8NS 
       13.48        16.47        13.22         7.76         8.71        13.41 
TCGA-L5-A8NV TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6L6 
       52.57        10.36        33.11         8.02         7.59         7.04 
TCGA-R6-A6XG TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WC TCGA-RE-A7BO 
       38.40         9.30        15.78         2.89         2.30         7.00 
TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX TCGA-VR-A8EQ TCGA-VR-AA4D 
        5.29        16.44         9.27         8.98        22.82        46.19 
TCGA-X8-AAAR TCGA-ZR-A9CJ 
       18.21        19.73 

$subtype2
TCGA-2H-A9GQ TCGA-IG-A5S3 TCGA-L5-A4OS TCGA-L5-A8NN TCGA-LN-A49L TCGA-LN-A49V 
        4.21        23.41        58.59         5.49        10.45        12.59 
TCGA-LN-A49Y TCGA-LN-A4A8 TCGA-LN-A7HY TCGA-LN-A9FO TCGA-R6-A6KZ TCGA-R6-A8WG 
       12.46        15.52        12.03         0.13         5.06        12.69 
TCGA-VR-A8EO TCGA-VR-A8Q7 
       25.81        52.27 

$subtype3
TCGA-IC-A6RF TCGA-L5-A43J TCGA-Q9-A6FU TCGA-IG-A3Y9 TCGA-IG-A50L TCGA-IG-A51D 
       15.68         4.31         5.16         0.85         0.53        17.03 
TCGA-IG-A5B8 TCGA-IG-A6QS TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FD TCGA-JY-A6FE 
        0.79         9.96        14.50        12.16        68.02         3.68 
TCGA-JY-A6FG TCGA-JY-A93F TCGA-L5-A88S TCGA-L5-A88W TCGA-LN-A49M TCGA-LN-A49O 
       41.52        24.03        15.48        25.12        12.66        13.41 
TCGA-LN-A49U TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A3 
       15.35        13.25        12.62        12.59        12.49        12.76 
TCGA-LN-A4A6 TCGA-LN-A4A9 TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV 
       12.85        11.54        13.22        12.33        25.25        10.52 
TCGA-LN-A7HX TCGA-LN-A9FR TCGA-V5-AASV TCGA-VR-A8ET TCGA-VR-A8EU TCGA-VR-A8EY 
       12.23        12.26        15.35         1.55        18.31        33.70 
TCGA-VR-AA4G TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I TCGA-Z6-A8JD TCGA-Z6-AAPN 
       18.05        11.24         9.17        15.91         3.42         2.66 

$subtype4
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A625 TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-L5-A43H 
       33.27        35.21        12.82         4.67        44.75         0.30 
TCGA-L5-A88Z TCGA-LN-A49K TCGA-LN-A49N TCGA-LN-A49P TCGA-LN-A49R TCGA-LN-A4A4 
        7.40         5.92        12.43        12.33        13.38        12.59 
TCGA-LN-A4MQ TCGA-LN-A5U5 TCGA-LN-A7HW TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A8I0 
       12.33         4.47        12.00        13.18        12.33        13.38 
TCGA-LN-A8I1 TCGA-LN-A9FQ TCGA-S8-A6BW TCGA-V5-A7RC TCGA-VR-A8ER TCGA-VR-A8EW 
       13.18        12.85        20.38         3.42        12.43         8.12 
TCGA-VR-A8EZ TCGA-XP-A8T6 TCGA-XP-A8T8 TCGA-Z6-A8JE TCGA-Z6-A9VB 
       18.18        25.08        14.37         2.10         1.32 

$subtype5
TCGA-L5-A8NT TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A93D 
       27.12        20.78         2.63         9.30        14.86        31.56 
TCGA-L5-A8NU TCGA-LN-A4A5 TCGA-LN-A9FP 
       83.24        22.39        12.03 

$subtype6
TCGA-L5-A88T TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-KH-A6WC TCGA-L5-A4OM TCGA-L5-A8NK 
       22.82        20.12        18.64         6.28        47.93        13.55 
TCGA-L5-A8NQ TCGA-L5-A8NW TCGA-L7-A56G TCGA-LN-A49S TCGA-Q9-A6FW TCGA-R6-A6L4 
       21.37        46.09        10.85        13.15         7.82        16.31 
TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-VR-A8EP TCGA-VR-A8EX 
        6.35        53.95        27.09        28.11 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
    0.36     0.13     0.53     0.30     2.63     6.28 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
  122.10    58.59    68.02    44.75    83.24    53.95 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
  13.710   12.525   12.640   12.430   20.780   19.380 
[1] "0.4 - 122.1 (13.7)" "0.1 - 58.6 (12.5)"  "0.5 - 68.0 (12.6)" 
[4] "0.3 - 44.8 (12.4)"  "2.6 - 83.2 (20.8)"  "6.3 - 54.0 (19.4)" 
D5V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       8        2        1        0         4        15        13
  subtype2       0        0        0        0         6         2         3
  subtype3       0        1        3        1        18         7         5
  subtype4       0        0        1        0        11         4         5
  subtype5       0        0        0        0         4         1         0
  subtype6       0        2        1        0         3         2         0
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          4          3          4        2         3
  subtype2          1          0          0        0         0
  subtype3          3          1          1        2         0
  subtype4          2          3          1        1         0
  subtype5          3          0          1        0         0
  subtype6          1          2          0        0         1
D5V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  STAGE I           8        0        0        0        0        0
  STAGE IA          2        0        1        0        0        2
  STAGE IB          1        0        3        1        0        1
  STAGE II          0        0        1        0        0        0
  STAGE IIA         4        6       18       11        4        3
  STAGE IIB        15        2        7        4        1        2
  STAGE III        13        3        5        5        0        0
  STAGE IIIA        4        1        3        2        3        1
  STAGE IIIB        3        0        1        3        0        2
  STAGE IIIC        4        0        1        1        1        0
  STAGE IV          2        0        2        1        0        0
  STAGE IVA         3        0        0        0        0        1
[1] 12  6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    24  6 34  0
  subtype2     0  4  8  0
  subtype3     3 14 23  2
  subtype4     2 10 15  1
  subtype5     0  4  3  2
  subtype6     3  4  5  0
D5V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  T0+T1       24        0        3        2        0        3
  T2           6        4       14       10        4        4
  T3          34        8       23       15        3        5
  T4           0        0        2        1        2        0
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1 20 35  5  4
  subtype2  7  5  0  0
  subtype3 27 10  2  2
  subtype4 11 13  3  1
  subtype5  6  1  0  1
  subtype6  5  5  2  0
D5V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  N0       20        7       27       11        6        5
  N1       35        5       10       13        1        5
  N2        5        0        2        3        0        2
  N3        4        0        2        1        1        0
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V6, binary
          cls
clus        0  1
  subtype1 43  5
  subtype2 12  0
  subtype3 36  2
  subtype4 26  1
  subtype5  8  0
  subtype6 10  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   43    5
  subtype2   12    0
  subtype3   36    2
  subtype4   26    1
  subtype5    8    0
  subtype6   10    1
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  0       43       12       36       26        8       10
  1        5        0        2        1        0        1
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V7, binary
          cls
clus        0  1
  subtype1 10 64
  subtype2  2 12
  subtype3  7 35
  subtype4  3 26
  subtype5  2  7
  subtype6  2 14
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10   64
  subtype2    2   12
  subtype3    7   35
  subtype4    3   26
  subtype5    2    7
  subtype6    2   14
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  FEMALE       10        2        7        3        2        2
  MALE         64       12       35       26        7       14
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V8, binary
          cls
clus        0  1
  subtype1 56  7
  subtype2 11  3
  subtype3 23 16
  subtype4 19  8
  subtype5  3  5
  subtype6 11  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   56    7
  subtype2   11    3
  subtype3   23   16
  subtype4   19    8
  subtype5    3    5
  subtype6   11    4
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  NO        56       11       23       19        3       11
  YES        7        3       16        8        5        4
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V9, continuous
D5V10, binary
          cls
clus        0  1
  subtype1 74  0
  subtype2  5  9
  subtype3  0 42
  subtype4  0 29
  subtype5  4  5
  subtype6  6 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   74    0
  subtype2    5    9
  subtype3    0   42
  subtype4    0   29
  subtype5    4    5
  subtype6    6   10
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA, NOS           74        5        0        0
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0        9       42       29
                                   clus
vv                                  subtype5 subtype6
  ESOPHAGUS ADENOCARCINOMA, NOS            4        6
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        5       10
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 52  7  0  2
  subtype2 11  0  0  0
  subtype3 35  1  1  3
  subtype4 22  3  1  1
  subtype5  7  1  0  0
  subtype6  9  1  0  1
D5V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  R0       52       11       35       22        7        9
  R1        7        0        1        3        1        1
  R2        0        0        1        1        0        0
  RX        2        0        3        1        0        1
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    57
  subtype2     6                         0     7
  subtype3    19                         1    21
  subtype4    17                         3     8
  subtype5     2                         0     7
  subtype6     1                         1    13
D5V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            1        6       19       17        2
  BLACK OR AFRICAN AMERICAN        0        0        1        3        0
  WHITE                           57        7       21        8        7
                           clus
vv                          subtype6
  ASIAN                            1
  BLACK OR AFRICAN AMERICAN        1
  WHITE                           13
[1] 3 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V15, binary
          cls
clus        0  1
  subtype1  2 17
  subtype2  1  8
  subtype3  0 27
  subtype4  2 21
  subtype5  0  6
  subtype6  0  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   17
  subtype2    1    8
  subtype3    0   27
  subtype4    2   21
  subtype5    0    6
  subtype6    0    9
                        clus
vv                       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  HISPANIC OR LATINO            2        1        0        2        0        0
  NOT HISPANIC OR LATINO       17        8       27       21        6        9
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(6) Variable = MRNASEQ_CHIERARCHICAL
D6V1, survival
          sevent
clus2       0  1
  subtype1 34 34
  subtype2 10 10
  subtype3 63 33
subtype1 subtype2 subtype3 
      68       20       96 
subtype1 subtype2 subtype3 
      34       10       33 
$subtype1
TCGA-JY-A6FB TCGA-JY-A938 TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OI TCGA-L5-A8NG 
       60.39        34.85        18.28         8.94        19.99        35.97 
TCGA-L5-A8NT TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ 
       27.12        25.78        20.05        31.27        14.30        58.55 
TCGA-2H-A9GK TCGA-2H-A9GL TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GR TCGA-IC-A6RE 
        7.63         5.92         8.94        16.24        32.45         7.69 
TCGA-IG-A7DP TCGA-JY-A6F8 TCGA-JY-A6FH TCGA-JY-A939 TCGA-JY-A93C TCGA-JY-A93D 
       14.86       122.10        47.38        21.70        23.18        31.56 
TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A4OF TCGA-L5-A4OH TCGA-L5-A4OJ 
       25.22         3.16        30.25        26.33        32.61        21.01 
TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS 
       18.35         3.32         7.17         1.38         3.16        58.59 
TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A891 TCGA-L5-A8NE 
        4.90        29.00         7.13         7.43         3.75        55.50 
TCGA-L5-A8NF TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM 
        2.66        12.92        13.48        16.47        13.22         7.76 
TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NU TCGA-L7-A6VZ TCGA-R6-A6DN 
        5.49         8.71        13.41        83.24        10.36         8.02 
TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6XG TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8WC 
        7.59         5.06        38.40         9.30        15.78         2.30 
TCGA-R6-A8WG TCGA-RE-A7BO TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX TCGA-VR-A8EQ 
       12.69         7.00        16.44         9.27         8.98        22.82 
TCGA-VR-AA4D TCGA-ZR-A9CJ 
       46.19        19.73 

$subtype2
TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A88T TCGA-L5-A88Y TCGA-S8-A6BV TCGA-2H-A9GM 
       24.00         4.70        22.82         0.36        20.02        13.94 
TCGA-IG-A4QS TCGA-L5-A88V TCGA-L5-A893 TCGA-L5-A8NV TCGA-L5-A8NW TCGA-M9-A5M8 
        3.88         2.60         3.02        52.57        46.09        33.11 
TCGA-Q9-A6FW TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A8W8 
        7.82        16.31         7.04         6.35        53.95         2.89 
TCGA-V5-A7RB TCGA-X8-AAAR 
        5.29        18.21 

$subtype3
TCGA-IC-A6RF TCGA-L5-A43J TCGA-Q9-A6FU TCGA-2H-A9GQ TCGA-IG-A3I8 TCGA-IG-A3QL 
       15.68         4.31         5.16         4.21        33.27        35.21 
TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A4QT 
        0.85        20.78         2.63        20.12        18.64         9.30 
TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS 
        0.53        17.03         0.79        23.41        12.82         9.96 
TCGA-IG-A8O2 TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE 
        4.67        14.50        12.16        44.75        68.02         3.68 
TCGA-JY-A6FG TCGA-JY-A93F TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A4OM TCGA-L5-A88S 
       41.52        24.03         6.28         0.30        47.93        15.48 
TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-L7-A56G TCGA-LN-A49K 
       25.12         7.40        13.55        21.37        10.85         5.92 
TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R 
       10.45        12.66        12.43        13.41        12.33        13.38 
TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y 
       13.15        15.35        12.59        13.25        12.62        12.46 
TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 
       12.59        12.49        12.76        12.59        22.39        12.85 
TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 
       15.52        11.54        12.33        13.22         4.47        12.33 
TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A7HZ 
       25.25        10.52        12.00        12.23        12.03        13.18 
TCGA-LN-A8HZ TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FP TCGA-LN-A9FQ 
       12.33        13.38        13.18         0.13        12.03        12.85 
TCGA-LN-A9FR TCGA-S8-A6BW TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EO TCGA-VR-A8EP 
       12.26        20.38         3.42        15.35        25.81        27.09 
TCGA-VR-A8ER TCGA-VR-A8ET TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8EX TCGA-VR-A8EY 
       12.43         1.55        18.31         8.12        28.11        33.70 
TCGA-VR-A8EZ TCGA-VR-A8Q7 TCGA-VR-AA4G TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I 
       18.18        52.27        18.05        11.24         9.17        15.91 
TCGA-XP-A8T6 TCGA-XP-A8T8 TCGA-Z6-A8JD TCGA-Z6-A8JE TCGA-Z6-A9VB TCGA-Z6-AAPN 
       25.08        14.37         3.42         2.10         1.32         2.66 

subtype1 subtype2 subtype3 
    1.38     0.36     0.13 
subtype1 subtype2 subtype3 
  122.10    53.95    68.02 
subtype1 subtype2 subtype3 
   15.32    10.88    12.64 
[1] "1.4 - 122.1 (15.3)" "0.4 - 54.0 (10.9)"  "0.1 - 68.0 (12.6)" 
D6V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       6        2        1        0         3        16        13
  subtype2       2        0        1        0         2         2         1
  subtype3       0        3        4        1        41        13        12
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          4          1          5        2         3
  subtype2          1          3          0        0         0
  subtype3          9          5          2        3         1
D6V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           6        2        0
  STAGE IA          2        0        3
  STAGE IB          1        1        4
  STAGE II          0        0        1
  STAGE IIA         3        2       41
  STAGE IIB        16        2       13
  STAGE III        13        1       12
  STAGE IIIA        4        1        9
  STAGE IIIB        1        3        5
  STAGE IIIC        5        0        2
  STAGE IV          2        0        3
  STAGE IVA         3        0        1
[1] 12  3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    18  9 30  1
  subtype2     6  2  7  0
  subtype3     8 31 51  4
D6V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       18        6        8
  T2           9        2       31
  T3          30        7       51
  T4           1        0        4
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1 17 32  3  5
  subtype2  5  7  3  0
  subtype3 54 30  6  3
D6V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       17        5       54
  N1       32        7       30
  N2        3        3        6
  N3        5        0        3
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V6, binary
          cls
clus        0  1
  subtype1 42  5
  subtype2  9  0
  subtype3 84  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   42    5
  subtype2    9    0
  subtype3   84    4
   clus
vv  subtype1 subtype2 subtype3
  0       42        9       84
  1        5        0        4
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V7, binary
          cls
clus        0  1
  subtype1 10 58
  subtype2  2 18
  subtype3 14 82
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10   58
  subtype2    2   18
  subtype3   14   82
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       10        2       14
  MALE         58       18       82
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V8, binary
          cls
clus        0  1
  subtype1 48  9
  subtype2 19  0
  subtype3 56 34
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   48    9
  subtype2   19    0
  subtype3   56   34
     clus
vv    subtype1 subtype2 subtype3
  NO        48       19       56
  YES        9        0       34
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V9, continuous
[1] "Remove cluster labels:" "subtype2"              
clus
subtype1 subtype2 subtype3 
       6        1       60 
 [1] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
 [7] "subtype3" "subtype3" "subtype1" "subtype3" "subtype3" "subtype3"
[13] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[19] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[25] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[31] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[37] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[43] "subtype1" "subtype3" "subtype1" "subtype1" "subtype3" "subtype3"
[49] "subtype1" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[55] "subtype3" "subtype3" "subtype3" "subtype1" "subtype3" "subtype3"
[61] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
D6V10, binary
          cls
clus        0  1
  subtype1 68  0
  subtype2 20  0
  subtype3  1 95
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   68    0
  subtype2   20    0
  subtype3    1   95
                                   clus
vv                                  subtype1 subtype2 subtype3
  ESOPHAGUS ADENOCARCINOMA, NOS           68       20        1
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0        0       95
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 46  8  0  1
  subtype2 12  0  0  2
  subtype3 78  5  2  4
D6V12, multiclass
    clus
vv   subtype1 subtype2 subtype3
  R0       46       12       78
  R1        8        0        5
  R2        0        0        2
  RX        1        2        4
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    54
  subtype2     0                         0    17
  subtype3    45                         5    42
D6V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        0       45
  BLACK OR AFRICAN AMERICAN        0        0        5
  WHITE                           54       17       42
[1] 3 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V15, binary
          cls
clus        0  1
  subtype1  2 14
  subtype2  1  9
  subtype3  2 65
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   14
  subtype2    1    9
  subtype3    2   65
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            2        1        2
  NOT HISPANIC OR LATINO       14        9       65
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(7) Variable = MIRSEQ_CNMF
D7V1, survival
          sevent
clus2       0  1
  subtype1 36 35
  subtype2  6  9
  subtype3  4  6
  subtype4 12  6
  subtype5 20  8
  subtype6 29 13
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
      71       15       10       18       28       42 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
      35        9        6        6        8       13 
$subtype1
TCGA-JY-A6FB TCGA-JY-A938 TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OG 
       60.39        34.85        18.28         8.94        24.00         4.70 
TCGA-L5-A4OI TCGA-L5-A88Y TCGA-L5-A8NG TCGA-L5-A8NT TCGA-S8-A6BV TCGA-2H-A9GF 
       19.99         0.36        35.97        27.12        20.02        25.78 
TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GM 
       20.05        31.27        14.30        58.55         7.63        13.94 
TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A4QS TCGA-JY-A6F8 
        8.94        16.24        32.45         7.69         3.88       122.10 
TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A4OH TCGA-L5-A4OJ 
       47.38        23.18         3.16        30.25        32.61        21.01 
TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP TCGA-L5-A4OR TCGA-L5-A4OW TCGA-L5-A4OX 
       18.35         3.32         7.17         3.16         7.13         7.43 
TCGA-L5-A88V TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH 
        2.60         3.75         3.02        55.50         2.66        12.92 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NR TCGA-L5-A8NV 
       13.48        16.47        13.22         7.76         8.71        52.57 
TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DQ TCGA-R6-A6L4 
       46.09        10.36        33.11         7.82         7.59        16.31 
TCGA-R6-A6L6 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-R6-A8W5 
        7.04        38.40         6.35        53.95         9.30        15.78 
TCGA-R6-A8W8 TCGA-R6-A8WC TCGA-R6-A8WG TCGA-RE-A7BO TCGA-V5-A7RE TCGA-V5-AASW 
        2.89         2.30        12.69         7.00        16.44         9.27 
TCGA-V5-AASX TCGA-VR-A8EQ TCGA-VR-AA4D TCGA-X8-AAAR TCGA-ZR-A9CJ 
        8.98        22.82        46.19        18.21        19.73 

$subtype2
TCGA-2H-A9GL TCGA-JY-A6FE TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L7-A56G TCGA-LN-A49O 
        5.92         3.68         4.90        29.00        10.85        13.41 
TCGA-LN-A5U7 TCGA-LN-A9FO TCGA-R6-A6DN TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8ER 
       25.25         0.13         8.02         3.42        15.35        12.43 
TCGA-VR-A8EZ TCGA-VR-A8Q7 TCGA-VR-AA7D 
       18.18        52.27         9.17 

$subtype3
TCGA-2H-A9GQ TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-L5-A4OF TCGA-L5-A4OQ TCGA-L5-A8NN 
        4.21         4.67        44.75        26.33         1.38         5.49 
TCGA-LN-A49S TCGA-R6-A6KZ TCGA-VR-AA7B TCGA-Z6-A8JE 
       13.15         5.06        11.24         2.10 

$subtype4
TCGA-IC-A6RF TCGA-IG-A3QL TCGA-IG-A4QT TCGA-IG-A5S3 TCGA-IG-A625 TCGA-L5-A4OM 
       15.68        35.21         9.30        23.41        12.82        47.93 
TCGA-L5-A4OS TCGA-L5-A88Z TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49Y TCGA-LN-A4A6 
       58.59         7.40         5.92        10.45        12.46        12.85 
TCGA-LN-A4A8 TCGA-LN-A4MQ TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A9FQ TCGA-V5-A7RB 
       15.52        12.33        13.18        12.33        12.85         5.29 

$subtype5
TCGA-L5-A88T TCGA-IG-A3I8 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4P3 TCGA-IG-A50L 
       22.82        33.27        20.78         2.63        18.64         0.53 
TCGA-IG-A7DP TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E TCGA-KH-A6WC TCGA-L5-A43H 
       14.86        21.70        31.56        25.22         6.28         0.30 
TCGA-L5-A88S TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-L5-A8NS TCGA-L5-A8NU TCGA-LN-A49N 
       15.48        13.55        21.37        13.41        83.24        12.43 
TCGA-LN-A49P TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A5 TCGA-LN-A7HY TCGA-LN-A9FP 
       12.33        13.25        12.62        22.39        12.03        12.03 
TCGA-LN-A9FR TCGA-VR-A8EX TCGA-XP-A8T6 TCGA-Z6-A8JD 
       12.26        28.11        25.08         3.42 

$subtype6
TCGA-L5-A43J TCGA-Q9-A6FU TCGA-IG-A3Y9 TCGA-IG-A3YC TCGA-IG-A51D TCGA-IG-A5B8 
        4.31         5.16         0.85        20.12        17.03         0.79 
TCGA-IG-A6QS TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FD TCGA-JY-A6FG TCGA-JY-A93F 
        9.96        14.50        12.16        68.02        41.52        24.03 
TCGA-L5-A88W TCGA-LN-A49M TCGA-LN-A49R TCGA-LN-A49U TCGA-LN-A4A1 TCGA-LN-A4A2 
       25.12        12.66        13.38        15.35        12.59        12.49 
TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A9 TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 
       12.76        12.59        11.54        13.22         4.47        12.33 
TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-S8-A6BW 
       10.52        12.00        12.23        13.38        13.18        20.38 
TCGA-VR-A8EO TCGA-VR-A8EP TCGA-VR-A8ET TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8EY 
       25.81        27.09         1.55        18.31         8.12        33.70 
TCGA-VR-AA4G TCGA-VR-AA7I TCGA-XP-A8T7 TCGA-XP-A8T8 TCGA-Z6-A9VB TCGA-Z6-AAPN 
       18.05        15.91        41.23        14.37         1.32         2.66 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
    0.36     0.13     1.38     5.29     0.30     0.79 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
  122.10    52.27    44.75    58.59    83.24    68.02 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
  14.300   10.850    5.275   12.835   14.205   12.970 
[1] "0.4 - 122.1 (14.3)" "0.1 - 52.3 (10.8)"  "1.4 - 44.8 (5.3)"  
[4] "5.3 - 58.6 (12.8)"  "0.3 - 83.2 (14.2)"  "0.8 - 68.0 (13.0)" 
D7V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       8        2        2        0         3        13        12
  subtype2       0        0        0        0         4         1         3
  subtype3       0        0        0        0         1         2         2
  subtype4       0        2        0        1        10         2         1
  subtype5       0        1        1        0         8         8         3
  subtype6       0        0        3        0        20         5         5
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          4          4        1         3
  subtype2          1          0          2        1         0
  subtype3          2          1          0        1         0
  subtype4          0          1          0        0         0
  subtype5          5          0          1        0         1
  subtype6          4          3          0        2         0
D7V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  STAGE I           8        0        0        0        0        0
  STAGE IA          2        0        0        2        1        0
  STAGE IB          2        0        0        0        1        3
  STAGE II          0        0        0        1        0        0
  STAGE IIA         3        4        1       10        8       20
  STAGE IIB        13        1        2        2        8        5
  STAGE III        12        3        2        1        3        5
  STAGE IIIA        2        1        2        0        5        4
  STAGE IIIB        4        0        1        1        0        3
  STAGE IIIC        4        2        0        0        1        0
  STAGE IV          1        1        1        0        0        2
  STAGE IVA         3        0        0        0        1        0
[1] 12  6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    21  6 31  0
  subtype2     0  2  9  1
  subtype3     1  2  6  0
  subtype4     4  7  7  0
  subtype5     3 10 13  2
  subtype6     3 16 21  2
D7V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  T0+T1       21        0        1        4        3        3
  T2           6        2        2        7       10       16
  T3          31        9        6        7       13       21
  T4           0        1        0        0        2        2
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1 19 30  5  4
  subtype2  5  5  0  2
  subtype3  1  5  2  1
  subtype4 13  4  1  0
  subtype5 13 13  0  1
  subtype6 25 12  4  0
D7V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  N0       19        5        1       13       13       25
  N1       30        5        5        4       13       12
  N2        5        0        2        1        0        4
  N3        4        2        1        0        1        0
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V6, binary
          cls
clus        0  1
  subtype1 41  4
  subtype2 10  1
  subtype3  6  1
  subtype4 16  0
  subtype5 25  1
  subtype6 37  2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   41    4
  subtype2   10    1
  subtype3    6    1
  subtype4   16    0
  subtype5   25    1
  subtype6   37    2
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  0       41       10        6       16       25       37
  1        4        1        1        0        1        2
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V7, binary
          cls
clus        0  1
  subtype1 10 61
  subtype2  0 15
  subtype3  1  9
  subtype4  5 13
  subtype5  4 24
  subtype6  7 35
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10   61
  subtype2    0   15
  subtype3    1    9
  subtype4    5   13
  subtype5    4   24
  subtype6    7   35
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  FEMALE       10        0        1        5        4        7
  MALE         61       15        9       13       24       35
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V8, binary
          cls
clus        0  1
  subtype1 54  7
  subtype2  8  6
  subtype3  8  1
  subtype4 14  3
  subtype5 15 10
  subtype6 25 15
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   54    7
  subtype2    8    6
  subtype3    8    1
  subtype4   14    3
  subtype5   15   10
  subtype6   25   15
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  NO        54        8        8       14       15       25
  YES        7        6        1        3       10       15
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V9, continuous
D7V10, binary
          cls
clus        0  1
  subtype1 71  0
  subtype2  4 11
  subtype3  5  5
  subtype4  2 16
  subtype5  7 21
  subtype6  0 42
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   71    0
  subtype2    4   11
  subtype3    5    5
  subtype4    2   16
  subtype5    7   21
  subtype6    0   42
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA, NOS           71        4        5        2
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0       11        5       16
                                   clus
vv                                  subtype5 subtype6
  ESOPHAGUS ADENOCARCINOMA, NOS            7        0
  ESOPHAGUS SQUAMOUS CELL CARCINOMA       21       42
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 47  6  0  3
  subtype2  8  3  0  0
  subtype3  7  0  0  1
  subtype4 17  0  0  0
  subtype5 22  3  0  0
  subtype6 35  1  2  3
D7V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  R0       47        8        7       17       22       35
  R1        6        3        0        0        3        1
  R2        0        0        0        0        0        2
  RX        3        0        1        0        0        3
[1] 4 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    56
  subtype2     3                         3     6
  subtype3     3                         0     6
  subtype4    10                         0     7
  subtype5     9                         1    17
  subtype6    19                         1    22
D7V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            1        3        3       10        9
  BLACK OR AFRICAN AMERICAN        0        3        0        0        1
  WHITE                           56        6        6        7       17
                           clus
vv                          subtype6
  ASIAN                           19
  BLACK OR AFRICAN AMERICAN        1
  WHITE                           22
[1] 3 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V15, binary
          cls
clus        0  1
  subtype1  2 20
  subtype2  0  7
  subtype3  0  4
  subtype4  1 14
  subtype5  1 15
  subtype6  2 27
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   20
  subtype2    0    7
  subtype3    0    4
  subtype4    1   14
  subtype5    1   15
  subtype6    2   27
                        clus
vv                       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  HISPANIC OR LATINO            2        0        0        1        1        2
  NOT HISPANIC OR LATINO       20        7        4       14       15       27
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(8) Variable = MIRSEQ_CHIERARCHICAL
D8V1, survival
          sevent
clus2       0  1
  subtype1 25 38
  subtype2 19  7
  subtype3 40 22
  subtype4 23 10
subtype1 subtype2 subtype3 subtype4 
      63       26       62       33 
subtype1 subtype2 subtype3 subtype4 
      38        7       22       10 
$subtype1
TCGA-JY-A6FB TCGA-L5-A43I TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A4OI TCGA-L5-A88Y 
       60.39        18.28        24.00         4.70        19.99         0.36 
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL 
       25.78        20.05        14.30        58.55         7.63         5.92 
TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GQ TCGA-IG-A4QS TCGA-JY-A6F8 
       13.94         8.94        16.24         4.21         3.88       122.10 
TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43E TCGA-L5-A4OF TCGA-L5-A4OH TCGA-L5-A4OJ 
       47.38        23.18        30.25        26.33        32.61        21.01 
TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OW 
       18.35         7.17         1.38         3.16        58.59         7.13 
TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH 
        7.43         2.60         3.75        55.50         2.66        12.92 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NW TCGA-L7-A6VZ 
       13.48        16.47         7.76         5.49        46.09        10.36 
TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG 
       33.11         8.02         5.06        16.31         7.04        38.40 
TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WC 
        6.35        53.95         9.30        15.78         2.89         2.30 
TCGA-R6-A8WG TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX 
       12.69         7.00         5.29        16.44         9.27         8.98 
TCGA-VR-A8EQ TCGA-VR-AA4D TCGA-ZR-A9CJ 
       22.82        46.19        19.73 

$subtype2
TCGA-JY-A938 TCGA-L5-A43M TCGA-L5-A88T TCGA-L5-A8NG TCGA-L5-A8NT TCGA-S8-A6BV 
       34.85         8.94        22.82        35.97        27.12        20.02 
TCGA-2H-A9GH TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A7DP TCGA-JY-A939 TCGA-JY-A93D 
       31.27        32.45         7.69        14.86        21.70        31.56 
TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A4OO TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A893 
       25.22         3.16         3.32         4.90        29.00         3.02 
TCGA-L5-A8NL TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NU TCGA-L5-A8NV TCGA-Q9-A6FW 
       13.22         8.71        13.41        83.24        52.57         7.82 
TCGA-R6-A6DQ TCGA-X8-AAAR 
        7.59        18.21 

$subtype3
TCGA-IC-A6RF TCGA-L5-A43J TCGA-Q9-A6FU TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 
       15.68         4.31         5.16        33.27        35.21         0.85 
TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4P3 TCGA-IG-A4QT TCGA-IG-A50L TCGA-IG-A5S3 
       20.78         2.63        18.64         9.30         0.53        23.41 
TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FE TCGA-KH-A6WC 
       12.82         9.96        14.50        12.16         3.68         6.28 
TCGA-L5-A43H TCGA-L5-A88S TCGA-L5-A88Z TCGA-L5-A8NQ TCGA-L7-A56G TCGA-LN-A49K 
        0.30        15.48         7.40        21.37        10.85         5.92 
TCGA-LN-A49L TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R TCGA-LN-A49W 
       10.45        12.43        13.41        12.33        13.38        13.25 
TCGA-LN-A49X TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 
       12.62        12.59        12.49        12.59        22.39        12.85 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A7HY TCGA-LN-A7HZ 
       12.33        13.22         4.47        12.33        12.03        13.18 
TCGA-LN-A8HZ TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FP TCGA-LN-A9FQ 
       12.33        13.38        13.18         0.13        12.03        12.85 
TCGA-LN-A9FR TCGA-S8-A6BW TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EP TCGA-VR-A8ER 
       12.26        20.38         3.42        15.35        27.09        12.43 
TCGA-VR-A8ET TCGA-VR-A8EW TCGA-VR-A8EZ TCGA-VR-AA4G TCGA-VR-AA7D TCGA-VR-AA7I 
        1.55         8.12        18.18        18.05         9.17        15.91 
TCGA-XP-A8T8 TCGA-Z6-A9VB 
       14.37         1.32 

$subtype4
TCGA-IG-A3YC TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-JY-A6FD 
       20.12        17.03         0.79         4.67        44.75        68.02 
TCGA-JY-A6FG TCGA-JY-A93F TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A8NK TCGA-LN-A49M 
       41.52        24.03        47.93        25.12        13.55        12.66 
TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49Y TCGA-LN-A4A3 TCGA-LN-A4A8 TCGA-LN-A4A9 
       13.15        15.35        12.46        12.76        15.52        11.54 
TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX TCGA-VR-A8EO TCGA-VR-A8EU 
       25.25        10.52        12.00        12.23        25.81        18.31 
TCGA-VR-A8EX TCGA-VR-A8EY TCGA-VR-A8Q7 TCGA-VR-AA7B TCGA-XP-A8T6 TCGA-XP-A8T7 
       28.11        33.70        52.27        11.24        25.08        41.23 
TCGA-Z6-A8JD TCGA-Z6-A8JE TCGA-Z6-AAPN 
        3.42         2.10         2.66 

subtype1 subtype2 subtype3 subtype4 
    0.36     3.02     0.13     0.79 
subtype1 subtype2 subtype3 subtype4 
  122.10    83.24    35.21    68.02 
subtype1 subtype2 subtype3 subtype4 
  13.480   19.115   12.460   15.520 
[1] "0.4 - 122.1 (13.5)" "3.0 - 83.2 (19.1)"  "0.1 - 35.2 (12.5)" 
[4] "0.8 - 68.0 (15.5)" 
D8V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        2        0         1        11        12
  subtype2       1        0        0        0         4         7         3
  subtype3       0        2        2        1        24         9         9
  subtype4       0        1        2        0        17         4         2
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          3          3        1         3
  subtype2          3          1          2        1         0
  subtype3          6          4          2        1         0
  subtype4          3          1          0        2         1
D8V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           7        1        0        0
  STAGE IA          2        0        2        1
  STAGE IB          2        0        2        2
  STAGE II          0        0        1        0
  STAGE IIA         1        4       24       17
  STAGE IIB        11        7        9        4
  STAGE III        12        3        9        2
  STAGE IIIA        2        3        6        3
  STAGE IIIB        3        1        4        1
  STAGE IIIC        3        2        2        0
  STAGE IV          1        1        1        2
  STAGE IVA         3        0        0        1
[1] 12  4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    19  8 23  0
  subtype2     5  3 15  1
  subtype3     4 21 31  4
  subtype4     4 11 18  0
D8V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1       19        5        4        4
  T2           8        3       21       11
  T3          23       15       31       18
  T4           0        1        4        0
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1 14 29  4  3
  subtype2  8 11  2  2
  subtype3 33 19  5  2
  subtype4 21 10  1  1
D8V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       14        8       33       21
  N1       29       11       19       10
  N2        4        2        5        1
  N3        3        2        2        1
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V6, binary
          cls
clus        0  1
  subtype1 33  4
  subtype2 19  1
  subtype3 55  1
  subtype4 28  3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   33    4
  subtype2   19    1
  subtype3   55    1
  subtype4   28    3
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       33       19       55       28
  1        4        1        1        3
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V7, binary
          cls
clus        0  1
  subtype1  7 56
  subtype2  5 21
  subtype3  8 54
  subtype4  7 26
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7   56
  subtype2    5   21
  subtype3    8   54
  subtype4    7   26
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        7        5        8        7
  MALE         56       21       54       26
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V8, binary
          cls
clus        0  1
  subtype1 49  6
  subtype2 19  3
  subtype3 34 24
  subtype4 22  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   49    6
  subtype2   19    3
  subtype3   34   24
  subtype4   22    9
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        49       19       34       22
  YES        6        3       24        9
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V9, continuous
[1] "Remove cluster labels:" "subtype2"              
clus
subtype1 subtype2 subtype3 subtype4 
       6        1       37       23 
 [1] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype4"
 [7] "subtype4" "subtype3" "subtype3" "subtype3" "subtype3" "subtype4"
[13] "subtype3" "subtype3" "subtype3" "subtype3" "subtype4" "subtype4"
[19] "subtype3" "subtype3" "subtype4" "subtype3" "subtype3" "subtype4"
[25] "subtype3" "subtype3" "subtype3" "subtype4" "subtype4" "subtype3"
[31] "subtype3" "subtype3" "subtype3" "subtype4" "subtype4" "subtype4"
[37] "subtype4" "subtype3" "subtype3" "subtype1" "subtype3" "subtype1"
[43] "subtype3" "subtype1" "subtype1" "subtype4" "subtype3" "subtype1"
[49] "subtype3" "subtype3" "subtype4" "subtype3" "subtype4" "subtype4"
[55] "subtype3" "subtype4" "subtype1" "subtype3" "subtype4" "subtype3"
[61] "subtype3" "subtype4" "subtype4" "subtype3" "subtype4" "subtype4"
D8V10, binary
          cls
clus        0  1
  subtype1 63  0
  subtype2 26  0
  subtype3  0 62
  subtype4  0 33
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   63    0
  subtype2   26    0
  subtype3    0   62
  subtype4    0   33
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA, NOS           63       26        0        0
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0        0       62       33
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 41  5  0  1
  subtype2 18  3  0  2
  subtype3 48  3  2  2
  subtype4 29  2  0  2
D8V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  R0       41       18       48       29
  R1        5        3        3        2
  R2        0        0        2        0
  RX        1        2        2        2
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    49
  subtype2     0                         0    22
  subtype3    30                         4    26
  subtype4    14                         1    17
D8V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            1        0       30       14
  BLACK OR AFRICAN AMERICAN        0        0        4        1
  WHITE                           49       22       26       17
[1] 3 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V15, binary
          cls
clus        0  1
  subtype1  3 17
  subtype2  0  6
  subtype3  1 46
  subtype4  2 18
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   17
  subtype2    0    6
  subtype3    1   46
  subtype4    2   18
                        clus
vv                       subtype1 subtype2 subtype3 subtype4
  HISPANIC OR LATINO            3        0        1        2
  NOT HISPANIC OR LATINO       17        6       46       18
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(9) Variable = MIRSEQ_MATURE_CNMF
D9V1, survival
          sevent
clus2       0  1
  subtype1 30 35
  subtype2 42 25
  subtype3 24 11
  subtype4  6  6
subtype1 subtype2 subtype3 subtype4 
      65       67       35       12 
subtype1 subtype2 subtype3 subtype4 
      35       25       11        6 
$subtype1
TCGA-JY-A6FB TCGA-JY-A938 TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OG 
       60.39        34.85        18.28         8.94        24.00         4.70 
TCGA-L5-A4OI TCGA-L5-A88Y TCGA-S8-A6BV TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH 
       19.99         0.36        20.02        25.78        20.05        31.27 
TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN 
       14.30        58.55         7.63         5.92        13.94         8.94 
TCGA-2H-A9GO TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43E 
       16.24         3.88       122.10        47.38        23.18        30.25 
TCGA-L5-A4OH TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS 
       32.61        18.35         7.17         1.38         3.16        58.59 
TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A891 
        4.90        29.00         7.13         7.43         2.60         3.75 
TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ 
        3.02        55.50         2.66        12.92        13.48        16.47 
TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 
        7.76         5.49         8.71        46.09        10.36        33.11 
TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 
        8.02         7.59        16.31        38.40         6.35        53.95 
TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WG TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-A7RE 
       15.78         2.89        12.69         7.00         5.29        16.44 
TCGA-V5-AASW TCGA-V5-AASX TCGA-VR-A8EQ TCGA-VR-AA4D TCGA-X8-AAAR 
        9.27         8.98        22.82        46.19        18.21 

$subtype2
TCGA-IC-A6RF TCGA-L5-A43J TCGA-Q9-A6FU TCGA-2H-A9GQ TCGA-IG-A3QL TCGA-IG-A4P3 
       15.68         4.31         5.16         4.21        35.21        18.64 
TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 
        0.53        17.03         0.79        12.82         9.96         4.67 
TCGA-IG-A97H TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-L5-A4OM 
       14.50        44.75        68.02         3.68        41.52        47.93 
TCGA-L5-A88W TCGA-L5-A88Z TCGA-L7-A56G TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M 
       25.12         7.40        10.85         5.92        10.45        12.66 
TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49Y TCGA-LN-A4A1 
       13.41        13.38        13.15        15.35        12.46        12.59 
TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ 
       12.49        12.59        12.85        15.52        11.54        12.33 
TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW 
       13.22         4.47        12.33        25.25        10.52        12.00 
TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A8I0 TCGA-LN-A8I1 
       12.23        12.03        13.18        12.33        13.38        13.18 
TCGA-LN-A9FO TCGA-LN-A9FQ TCGA-S8-A6BW TCGA-V5-A7RC TCGA-VR-A8EO TCGA-VR-A8EP 
        0.13        12.85        20.38         3.42        25.81        27.09 
TCGA-VR-A8ER TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8EX TCGA-VR-A8EY TCGA-VR-A8EZ 
       12.43        18.31         8.12        28.11        33.70        18.18 
TCGA-VR-A8Q7 TCGA-VR-AA7B TCGA-VR-AA7D TCGA-XP-A8T7 TCGA-XP-A8T8 TCGA-Z6-A9VB 
       52.27        11.24         9.17        41.23        14.37         1.32 
TCGA-Z6-AAPN 
        2.66 

$subtype3
TCGA-L5-A88T TCGA-L5-A8NG TCGA-L5-A8NT TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A3I8 
       22.82        35.97        27.12        32.45         7.69        33.27 
TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC TCGA-IG-A4QT TCGA-IG-A5S3 TCGA-IG-A7DP 
       20.78         2.63        20.12         9.30        23.41        14.86 
TCGA-IG-A97I TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E TCGA-KH-A6WC TCGA-L5-A43H 
       12.16        21.70        31.56        25.22         6.28         0.30 
TCGA-L5-A4OF TCGA-L5-A4OO TCGA-L5-A88S TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-L5-A8NS 
       26.33         3.32        15.48        13.55        21.37        13.41 
TCGA-L5-A8NU TCGA-L5-A8NV TCGA-LN-A49N TCGA-LN-A49P TCGA-LN-A49W TCGA-LN-A49X 
       83.24        52.57        12.43        12.33        13.25        12.62 
TCGA-LN-A4A5 TCGA-LN-A9FP TCGA-Q9-A6FW TCGA-R6-A6KZ TCGA-XP-A8T6 
       22.39        12.03         7.82         5.06        25.08 

$subtype4
TCGA-IG-A3Y9 TCGA-L5-A43C TCGA-L5-A8NL TCGA-LN-A9FR TCGA-R6-A6L6 TCGA-R6-A6Y2 
        0.85         3.16        13.22        12.26         7.04         9.30 
TCGA-VR-A8ET TCGA-VR-AA4G TCGA-VR-AA7I TCGA-Z6-A8JD TCGA-Z6-A8JE TCGA-ZR-A9CJ 
        1.55        18.05        15.91         3.42         2.10        19.73 

subtype1 subtype2 subtype3 subtype4 
    0.36     0.13     0.30     0.85 
subtype1 subtype2 subtype3 subtype4 
  122.10    68.02    83.24    19.73 
subtype1 subtype2 subtype3 subtype4 
   13.94    12.66    15.48     8.17 
[1] "0.4 - 122.1 (13.9)" "0.1 - 68.0 (12.7)"  "0.3 - 83.2 (15.5)" 
[4] "0.8 - 19.7 (8.2)"  
D9V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        2        0         2        12        12
  subtype2       0        2        2        1        31         7         8
  subtype3       0        1        1        0        12         9         3
  subtype4       0        0        0        0         1         2         2
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          3          3          2        2         3
  subtype2          3          5          2        3         1
  subtype3          5          1          2        0         0
  subtype4          3          0          1        0         0
D9V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           7        0        0        0
  STAGE IA          2        2        1        0
  STAGE IB          2        2        1        0
  STAGE II          0        1        0        0
  STAGE IIA         2       31       12        1
  STAGE IIB        12        7        9        2
  STAGE III        12        8        3        2
  STAGE IIIA        3        3        5        3
  STAGE IIIB        3        5        1        0
  STAGE IIIC        2        2        2        1
  STAGE IV          2        3        0        0
  STAGE IVA         3        1        0        0
[1] 12  4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    20  8 27  0
  subtype2     7 22 35  1
  subtype3     4  9 19  2
  subtype4     0  3  4  2
D9V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1       20        7        4        0
  T2           8       22        9        3
  T3          27       35       19        4
  T4           0        1        2        2
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1 16 32  5  2
  subtype2 35 21  5  3
  subtype3 18 12  1  2
  subtype4  4  3  1  1
D9V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       16       35       18        4
  N1       32       21       12        3
  N2        5        5        1        1
  N3        2        3        2        1
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V6, binary
          cls
clus        0  1
  subtype1 36  5
  subtype2 57  4
  subtype3 31  0
  subtype4  8  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   36    5
  subtype2   57    4
  subtype3   31    0
  subtype4    8    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       36       57       31        8
  1        5        4        0        0
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V7, binary
          cls
clus        0  1
  subtype1 10 55
  subtype2  9 58
  subtype3  5 30
  subtype4  1 11
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10   55
  subtype2    9   58
  subtype3    5   30
  subtype4    1   11
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       10        9        5        1
  MALE         55       58       30       11
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V8, binary
          cls
clus        0  1
  subtype1 51  6
  subtype2 40 22
  subtype3 21 11
  subtype4 10  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   51    6
  subtype2   40   22
  subtype3   21   11
  subtype4   10    1
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        51       40       21       10
  YES        6       22       11        1
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V9, continuous
D9V10, binary
          cls
clus        0  1
  subtype1 65  0
  subtype2  1 66
  subtype3 16 19
  subtype4  5  7
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   65    0
  subtype2    1   66
  subtype3   16   19
  subtype4    5    7
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA, NOS           65        1       16        5
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0       66       19        7
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 44  6  0  2
  subtype2 57  2  1  3
  subtype3 23  5  0  1
  subtype4  8  0  1  1
D9V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  R0       44       57       23        8
  R1        6        2        5        0
  R2        0        1        0        1
  RX        2        3        1        1
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    49
  subtype2    36                         3    24
  subtype3     6                         1    27
  subtype4     1                         0    11
D9V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            1       36        6        1
  BLACK OR AFRICAN AMERICAN        0        3        1        0
  WHITE                           49       24       27       11
[1] 3 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V15, binary
          cls
clus        0  1
  subtype1  2 16
  subtype2  2 45
  subtype3  1 17
  subtype4  1  6
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   16
  subtype2    2   45
  subtype3    1   17
  subtype4    1    6
                        clus
vv                       subtype1 subtype2 subtype3 subtype4
  HISPANIC OR LATINO            2        2        1        1
  NOT HISPANIC OR LATINO       16       45       17        6
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(10) Variable = MIRSEQ_MATURE_CHIERARCHICAL
D10V1, survival
          sevent
clus2       0  1
  subtype1 20 36
  subtype2 20  9
  subtype3 62 32
subtype1 subtype2 subtype3 
      56       29       94 
subtype1 subtype2 subtype3 
      36        9       32 
$subtype1
TCGA-JY-A6FB TCGA-L5-A43I TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A4OI TCGA-2H-A9GF 
       60.39        18.28        24.00         4.70        19.99        25.78 
TCGA-2H-A9GG TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL TCGA-2H-A9GM 
       20.05        14.30        58.55         7.63         5.92        13.94 
TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GQ TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FH 
        8.94        16.24         4.21         3.88       122.10        47.38 
TCGA-JY-A93C TCGA-L5-A43E TCGA-L5-A4OF TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ 
       23.18        30.25        26.33        18.35         7.17         1.38 
TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A891 TCGA-L5-A8NE 
        3.16        58.59         7.43         2.60         3.75        55.50 
TCGA-L5-A8NF TCGA-L5-A8NH TCGA-L5-A8NJ TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NW 
        2.66        12.92        16.47         7.76         5.49        46.09 
TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 
       10.36        33.11         8.02         5.06        16.31         7.04 
TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WG 
       38.40         6.35         9.30        15.78         2.89        12.69 
TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX TCGA-VR-A8EQ 
        7.00         5.29        16.44         9.27         8.98        22.82 
TCGA-VR-AA4D TCGA-ZR-A9CJ 
       46.19        19.73 

$subtype2
TCGA-JY-A938 TCGA-L5-A43M TCGA-L5-A88Y TCGA-L5-A8NG TCGA-L5-A8NT TCGA-S8-A6BV 
       34.85         8.94         0.36        35.97        27.12        20.02 
TCGA-2H-A9GH TCGA-2H-A9GR TCGA-IC-A6RE TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E 
       31.27        32.45         7.69        21.70        31.56        25.22 
TCGA-L5-A43C TCGA-L5-A4OH TCGA-L5-A4OO TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW 
        3.16        32.61         3.32         4.90        29.00         7.13 
TCGA-L5-A893 TCGA-L5-A8NI TCGA-L5-A8NL TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NU 
        3.02        13.48        13.22         8.71        13.41        83.24 
TCGA-L5-A8NV TCGA-Q9-A6FW TCGA-R6-A6DQ TCGA-R6-A6Y0 TCGA-X8-AAAR 
       52.57         7.82         7.59        53.95        18.21 

$subtype3
TCGA-IC-A6RF TCGA-L5-A43J TCGA-L5-A88T TCGA-Q9-A6FU TCGA-IG-A3I8 TCGA-IG-A3QL 
       15.68         4.31        22.82         5.16        33.27        35.21 
TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A4QT 
        0.85        20.78         2.63        20.12        18.64         9.30 
TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS 
        0.53        17.03         0.79        23.41        12.82         9.96 
TCGA-IG-A7DP TCGA-IG-A8O2 TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FA TCGA-JY-A6FD 
       14.86         4.67        14.50        12.16        44.75        68.02 
TCGA-JY-A6FE TCGA-JY-A6FG TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A4OM TCGA-L5-A88S 
        3.68        41.52         6.28         0.30        47.93        15.48 
TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-L7-A56G TCGA-LN-A49K 
       25.12         7.40        13.55        21.37        10.85         5.92 
TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R 
       10.45        12.66        12.43        13.41        12.33        13.38 
TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A1 
       13.15        15.35        13.25        12.62        12.46        12.59 
TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
       12.49        12.59        22.39        12.85        15.52        11.54 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV 
       12.33        13.22         4.47        12.33        25.25        10.52 
TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8HZ TCGA-LN-A8I0 
       12.00        12.23        12.03        13.18        12.33        13.38 
TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FP TCGA-LN-A9FQ TCGA-LN-A9FR TCGA-S8-A6BW 
       13.18         0.13        12.03        12.85        12.26        20.38 
TCGA-V5-A7RC TCGA-VR-A8EO TCGA-VR-A8EP TCGA-VR-A8ER TCGA-VR-A8ET TCGA-VR-A8EU 
        3.42        25.81        27.09        12.43         1.55        18.31 
TCGA-VR-A8EW TCGA-VR-A8EX TCGA-VR-A8EY TCGA-VR-A8EZ TCGA-VR-A8Q7 TCGA-VR-AA4G 
        8.12        28.11        33.70        18.18        52.27        18.05 
TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I TCGA-XP-A8T6 TCGA-XP-A8T7 TCGA-XP-A8T8 
       11.24         9.17        15.91        25.08        41.23        14.37 
TCGA-Z6-A8JD TCGA-Z6-A8JE TCGA-Z6-A9VB TCGA-Z6-AAPN 
        3.42         2.10         1.32         2.66 

subtype1 subtype2 subtype3 
    1.38     0.36     0.13 
subtype1 subtype2 subtype3 
  122.10    83.24    68.02 
subtype1 subtype2 subtype3 
   13.43    18.21    12.74 
[1] "1.4 - 122.1 (13.4)" "0.4 - 83.2 (18.2)"  "0.1 - 68.0 (12.7)" 
D10V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       5        2        2        0         1        10        11
  subtype2       2        0        0        0         4         7         4
  subtype3       0        3        3        1        41        13        10
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          3          3        1         3
  subtype2          2          1          2        1         0
  subtype3         10          5          2        3         1
D10V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           5        2        0
  STAGE IA          2        0        3
  STAGE IB          2        0        3
  STAGE II          0        0        1
  STAGE IIA         1        4       41
  STAGE IIB        10        7       13
  STAGE III        11        4       10
  STAGE IIIA        2        2       10
  STAGE IIIB        3        1        5
  STAGE IIIC        3        2        2
  STAGE IV          1        1        3
  STAGE IVA         3        0        1
[1] 12  3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T0+T1 T2 T3 T4
  subtype1    16  7 22  0
  subtype2     7  3 16  0
  subtype3     8 32 47  5
D10V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       16        7        8
  T2           7        3       32
  T3          22       16       47
  T4           0        0        5
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       N0 N1 N2 N3
  subtype1 11 27  4  3
  subtype2 10 12  2  2
  subtype3 52 29  6  3
D10V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       11       10       52
  N1       27       12       29
  N2        4        2        6
  N3        3        2        3
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V6, binary
          cls
clus        0  1
  subtype1 29  4
  subtype2 21  1
  subtype3 82  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   29    4
  subtype2   21    1
  subtype3   82    4
   clus
vv  subtype1 subtype2 subtype3
  0       29       21       82
  1        4        1        4
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V7, binary
          cls
clus        0  1
  subtype1  5 51
  subtype2  5 24
  subtype3 15 79
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5   51
  subtype2    5   24
  subtype3   15   79
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        5        5       15
  MALE         51       24       79
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V8, binary
          cls
clus        0  1
  subtype1 44  6
  subtype2 21  3
  subtype3 57 31
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   44    6
  subtype2   21    3
  subtype3   57   31
     clus
vv    subtype1 subtype2 subtype3
  NO        44       21       57
  YES        6        3       31
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V9, continuous
D10V10, binary
          cls
clus        0  1
  subtype1 56  0
  subtype2 29  0
  subtype3  2 92
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   56    0
  subtype2   29    0
  subtype3    2   92
                                   clus
vv                                  subtype1 subtype2 subtype3
  ESOPHAGUS ADENOCARCINOMA, NOS           56       29        2
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0        0       92
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 36  5  0  1
  subtype2 21  3  0  2
  subtype3 75  5  2  4
D10V12, multiclass
    clus
vv   subtype1 subtype2 subtype3
  R0       36       21       75
  R1        5        3        5
  R2        0        0        2
  RX        1        2        4
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    43
  subtype2     0                         0    24
  subtype3    43                         4    44
D10V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        0       43
  BLACK OR AFRICAN AMERICAN        0        0        4
  WHITE                           43       24       44
[1] 3 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V15, binary
          cls
clus        0  1
  subtype1  3 15
  subtype2  0  6
  subtype3  3 63
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   15
  subtype2    0    6
  subtype3    3   63
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            3        0        3
  NOT HISPANIC OR LATINO       15        6       63
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
