[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/19775149/ESCA-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/ESCA-TP/20125286/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 
65 44 75 
 1  2  3 
65 44 75 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3 
77 32 76 
 1  2  3 
77 32 76 
[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 
82 69 22 11 
 1  2  3  4 
82 69 22 11 
[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 
85 87 12 
 1  2  3 
85 87 12 
[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 
67 66 35 11 
 1  2  3  4 
67 66 35 11 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
 1  2  3 
63 22 94 
 1  2  3 
63 22 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=114,	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 29 36
  subtype2 31 13
  subtype3 47 27
subtype1 subtype2 subtype3 
      65       44       74 
subtype1 subtype2 subtype3 
      36       13       27 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL 
       25.78        31.27        14.30        58.55         7.63         5.92 
TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GQ TCGA-2H-A9GR TCGA-IG-A4QS TCGA-JY-A6F8 
       13.94         8.94         4.21        32.45         3.88       122.10 
TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE 
       60.39        47.38        23.18        18.28         8.94        24.00 
TCGA-L5-A4OH TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OT 
       32.61        18.35         7.17         1.38         3.16         4.90 
TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A8NE 
        7.13         7.43         2.60         0.36         3.75        55.50 
TCGA-L5-A8NF TCGA-L5-A8NG TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NN 
        2.66        35.97        12.92        13.48        16.47         5.49 
TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 
        8.71        13.41        27.12        46.09        10.36        33.11 
TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ 
        7.99         7.59         5.06        16.31        38.40         6.35 
TCGA-R6-A6Y0 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WC TCGA-R6-A8WG TCGA-RE-A7BO 
       53.95        15.78         2.89         2.30        12.69         7.00 
TCGA-S8-A6BV TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW TCGA-VR-AA4D TCGA-ZR-A9CJ 
       20.02         5.29        16.44         9.27        46.19        19.73 
TCGA-IG-A3QL TCGA-LN-A49L TCGA-LN-A49U TCGA-LN-A49V TCGA-VR-A8Q7 
       35.21        10.45        15.35        12.59        52.27 

$subtype2
TCGA-2H-A9GO TCGA-IC-A6RE TCGA-IG-A7DP TCGA-JY-A938 TCGA-JY-A939 TCGA-JY-A93D 
       16.24         7.69        14.86        34.85        21.70        31.56 
TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OI 
       25.22         3.16        30.25        26.33         4.70        19.99 
TCGA-L5-A4OJ TCGA-L5-A4OO TCGA-L5-A4OS TCGA-L5-A4OU TCGA-L5-A88T TCGA-L5-A893 
       21.01         3.32        58.59        29.00        22.82         3.02 
TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NU TCGA-Q9-A6FW TCGA-R6-A6L6 TCGA-R6-A6Y2 
       13.22         7.76        83.24         7.82         7.04         9.30 
TCGA-V5-AASX TCGA-VR-A8EQ TCGA-X8-AAAR TCGA-IC-A6RF TCGA-IG-A4QT TCGA-JY-A6FD 
        8.98        22.82        18.21        15.68         9.30        68.02 
TCGA-JY-A6FG TCGA-JY-A93F TCGA-KH-A6WC TCGA-L5-A88W TCGA-L5-A8NK TCGA-L5-A8NQ 
       41.52        24.03         6.28        25.12        13.55        21.37 
TCGA-LN-A49P TCGA-LN-A49X TCGA-LN-A9FP TCGA-V5-AASV TCGA-VR-A8EP TCGA-VR-A8ET 
       12.33        12.62        12.03        15.35        27.09         1.55 
TCGA-Z6-A8JD TCGA-Z6-AAPN 
        3.42         2.66 

$subtype3
TCGA-L5-A8NV TCGA-IG-A3I8 TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC 
       52.57        33.27         0.85        20.78         2.63        20.12 
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-A43J TCGA-L5-A4OM TCGA-L5-A88S TCGA-L5-A88Z TCGA-L7-A56G 
        0.30         4.31        47.93        15.48         7.40        10.85 
TCGA-LN-A49K TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S 
        5.92        12.66        12.43        13.41        13.38        13.15 
TCGA-LN-A49W TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 
       13.25        12.46        12.59        12.49        12.76        12.59 
TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR 
       22.39        12.85        15.52        11.54        12.33        13.22 
TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX 
        4.47        12.33        25.25        10.52        12.00        12.23 
TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FQ 
       12.03        13.18        13.38        13.18         0.13        12.85 
TCGA-LN-A9FR TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-A7RC TCGA-VR-A8EO TCGA-VR-A8ER 
       12.26         5.16        20.38         3.42        25.81        12.43 
TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8EX TCGA-VR-A8EY TCGA-VR-A8EZ TCGA-VR-AA4G 
       18.31         8.12        28.11        33.70        18.18        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-A8JE TCGA-Z6-A9VB 
        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 
  13.410   15.515   12.710 
[1] "0.4 - 122.1 (13.4)" "1.6 - 83.2 (15.5)"  "0.1 - 52.6 (12.7)" 
D1V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       4        2        2        0         6        11        12
  subtype2       4        2        1        0        12         9         3
  subtype3       0        1        3        1        29        11        10
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          4          3          2        2         2
  subtype2          2          2          3        0         1
  subtype3          8          4          2        3         1
D1V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           4        4        0
  STAGE IA          2        2        1
  STAGE IB          2        1        3
  STAGE II          0        0        1
  STAGE IIA         6       12       29
  STAGE IIB        11        9       11
  STAGE III        12        3       10
  STAGE IIIA        4        2        8
  STAGE IIIB        3        2        4
  STAGE IIIC        2        3        2
  STAGE IV          2        0        3
  STAGE IVA         2        1        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  8 30  0
  subtype2    10  9 20  1
  subtype3     6 26 37  4
D1V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       16       10        6
  T2           8        9       26
  T3          30       20       37
  T4           0        1        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 18 29  5  2
  subtype2 22 12  2  3
  subtype3 37 27  5  3
D1V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       18       22       37
  N1       29       12       27
  N2        5        2        5
  N3        2        3        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 37  4
  subtype2 33  1
  subtype3 65  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   37    4
  subtype2   33    1
  subtype3   65    4
   clus
vv  subtype1 subtype2 subtype3
  0       37       33       65
  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"
D1V7, binary
          cls
clus        0  1
  subtype1  6 59
  subtype2 11 33
  subtype3 10 65
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    6   59
  subtype2   11   33
  subtype3   10   65
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        6       11       10
  MALE         59       33       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"
D1V8, binary
          cls
clus        0  1
  subtype1 47 10
  subtype2 30  9
  subtype3 47 23
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   47   10
  subtype2   30    9
  subtype3   47   23
     clus
vv    subtype1 subtype2 subtype3
  NO        47       30       47
  YES       10        9       23
[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 60  5
  subtype2 27 17
  subtype3  1 74
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   60    5
  subtype2   27   17
  subtype3    1   74
                                   clus
vv                                  subtype1 subtype2 subtype3
  ESOPHAGUS ADENOCARCINOMA  NOS           60       27        1
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        5       17       74
[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 44  6  0  2
  subtype2 33  3  0  1
  subtype3 60  3  2  4
D1V12, multiclass
    clus
vv   subtype1 subtype2 subtype3
  R0       44       33       60
  R1        6        3        3
  R2        0        0        2
  RX        2        1        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     4                         0    46
  subtype2     4                         1    38
  subtype3    38                         4    30
D1V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            4        4       38
  BLACK OR AFRICAN AMERICAN        0        1        4
  WHITE                           46       38       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 21
  subtype2  1 15
  subtype3  3 52
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   21
  subtype2    1   15
  subtype3    3   52
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            2        1        3
  NOT HISPANIC OR LATINO       21       15       52
[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 37 40
  subtype2 22 10
  subtype3 48 27
subtype1 subtype2 subtype3 
      77       32       75 
subtype1 subtype2 subtype3 
      40       10       27 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A4QS 
        5.92        13.94         8.94        32.45         7.69         3.88 
TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A93C TCGA-JY-A93D 
      122.10        60.39        47.38        34.85        23.18        31.56 
TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43I TCGA-L5-A4OE TCGA-L5-A4OF 
       25.22         3.16        30.25        18.28        24.00        26.33 
TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OP 
        4.70        32.61        19.99        21.01        18.35         7.17 
TCGA-L5-A4OR TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V 
        3.16         4.90        29.00         7.13         7.43         2.60 
TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NG 
        0.36         3.75         3.02        55.50         2.66        35.97 
TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NN 
       12.92        13.48        16.47        13.22         7.76         5.49 
TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NV TCGA-L5-A8NW TCGA-L7-A6VZ 
        8.71        13.41        27.12        52.57        46.09        10.36 
TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 
       33.11         7.82         7.99         7.59         5.06        16.31 
TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WC 
       38.40         6.35         9.30        15.78         2.89         2.30 
TCGA-R6-A8WG TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW 
       12.69         7.00        20.02         5.29        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-A9GO TCGA-IG-A7DP TCGA-JY-A939 TCGA-L5-A43M TCGA-L5-A4OO TCGA-L5-A4OQ 
       16.24        14.86        21.70         8.94         3.32         1.38 
TCGA-L5-A4OS TCGA-L5-A88T TCGA-L5-A8NU TCGA-R6-A6L6 TCGA-R6-A6Y0 TCGA-IG-A3YA 
       58.59        22.82        83.24         7.04        53.95        20.78 
TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A4QT TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A97H 
       20.12        18.64         9.30         0.79        23.41        14.50 
TCGA-KH-A6WC TCGA-L5-A88S TCGA-L5-A8NQ TCGA-LN-A49P TCGA-LN-A49W TCGA-LN-A49X 
        6.28        15.48        21.37        12.33        13.25        12.62 
TCGA-LN-A4A3 TCGA-LN-A4A5 TCGA-LN-A7HY TCGA-LN-A9FP TCGA-VR-A8ET TCGA-VR-A8Q7 
       12.76        22.39        12.03        12.03         1.55        52.27 
TCGA-Z6-A8JD TCGA-Z6-AAPN 
        3.42         2.66 

$subtype3
TCGA-2H-A9GQ TCGA-IC-A6RF TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YB 
        4.21        15.68        33.27        35.21         0.85         2.63 
TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97I 
        0.53        17.03        12.82         9.96         4.67        12.16 
TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-JY-A93F TCGA-L5-A43H 
       44.75        68.02         3.68        41.52        24.03         0.30 
TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L7-A56G 
        4.31        47.93        25.12         7.40        13.55        10.85 
TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R 
        5.92        10.45        12.66        12.43        13.41        13.38 
TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4A2 
       13.15        15.35        12.59        12.46        12.59        12.49 
TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR 
       12.59        12.85        15.52        11.54        12.33        13.22 
TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX 
        4.47        12.33        25.25        10.52        12.00        12.23 
TCGA-LN-A7HZ TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FQ TCGA-LN-A9FR 
       13.18        13.38        13.18         0.13        12.85        12.26 
TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EO TCGA-VR-A8EP 
        5.16        20.38         3.42        15.35        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-AA4G TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I TCGA-XP-A8T6 TCGA-XP-A8T7 
       18.05        11.24         9.17        15.91        25.08        41.23 
TCGA-XP-A8T8 TCGA-Z6-A8JE TCGA-Z6-A9VB 
       14.37         2.10         1.32 

subtype1 subtype2 subtype3 
    0.36     0.79     0.13 
subtype1 subtype2 subtype3 
  122.10    83.24    68.02 
subtype1 subtype2 subtype3 
  13.940   13.875   12.660 
[1] "0.4 - 122.1 (13.9)" "0.8 - 83.2 (13.9)"  "0.1 - 68.0 (12.7)" 
D2V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       8        2        2        0         4        15        14
  subtype2       0        1        2        0        10         6         3
  subtype3       0        2        2        1        33        10         9
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          3          4          4        2         2
  subtype2          5          0          1        0         1
  subtype3          6          5          2        3         1
D2V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           8        0        0
  STAGE IA          2        1        2
  STAGE IB          2        2        2
  STAGE II          0        0        1
  STAGE IIA         4       10       33
  STAGE IIB        15        6       10
  STAGE III        14        3        9
  STAGE IIIA        3        5        6
  STAGE IIIB        4        0        5
  STAGE IIIC        4        1        2
  STAGE IV          2        0        3
  STAGE IVA         2        1        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    23  7 34  0
  subtype2     2  9 17  2
  subtype3     7 27 37  3
D2V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       23        2        7
  T2           7        9       27
  T3          34       17       37
  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 21 35  4  4
  subtype2 15 10  2  1
  subtype3 41 24  6  3
D2V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       21       15       41
  N1       35       10       24
  N2        4        2        6
  N3        4        1        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"
D2V6, binary
          cls
clus        0  1
  subtype1 46  4
  subtype2 25  1
  subtype3 65  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   46    4
  subtype2   25    1
  subtype3   65    4
   clus
vv  subtype1 subtype2 subtype3
  0       46       25       65
  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"
D2V7, binary
          cls
clus        0  1
  subtype1  9 68
  subtype2  5 27
  subtype3 13 63
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   68
  subtype2    5   27
  subtype3   13   63
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        9        5       13
  MALE         68       27       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"
D2V8, binary
          cls
clus        0  1
  subtype1 58  9
  subtype2 21  8
  subtype3 46 25
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   58    9
  subtype2   21    8
  subtype3   46   25
     clus
vv    subtype1 subtype2 subtype3
  NO        58       21       46
  YES        9        8       25
[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"
D2V9, continuous
D2V10, binary
          cls
clus        0  1
  subtype1 77  0
  subtype2 11 21
  subtype3  1 75
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   77    0
  subtype2   11   21
  subtype3    1   75
                                   clus
vv                                  subtype1 subtype2 subtype3
  ESOPHAGUS ADENOCARCINOMA  NOS           77       11        1
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0       21       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"
D2V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 52  7  0  2
  subtype2 24  1  0  1
  subtype3 61  5  2  4
D2V12, multiclass
    clus
vv   subtype1 subtype2 subtype3
  R0       52       24       61
  R1        7        1        5
  R2        0        0        2
  RX        2        1        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"
D2V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    62
  subtype2     8                         0    22
  subtype3    37                         5    30
D2V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        8       37
  BLACK OR AFRICAN AMERICAN        0        0        5
  WHITE                           62       22       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"
D2V15, binary
          cls
clus        0  1
  subtype1  3 20
  subtype2  0 19
  subtype3  3 49
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   20
  subtype2    0   19
  subtype3    3   49
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            3        0        3
  NOT HISPANIC OR LATINO       20       19       49
[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(3) Variable = RPPA_CNMF
D3V1, survival
          sevent
clus2       0  1
  subtype1 13 13
  subtype2 21  7
  subtype3 19 11
  subtype4 24  9
  subtype5  4  4
subtype1 subtype2 subtype3 subtype4 subtype5 
      26       28       30       33        8 
subtype1 subtype2 subtype3 subtype4 subtype5 
      13        7       11        9        4 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A4QS TCGA-JY-A939 TCGA-L5-A43E 
       25.78        32.45         7.69         3.88        21.70        30.25 
TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OH TCGA-L5-A4OJ TCGA-L5-A4ON 
       18.28         8.94        24.00        32.61        21.01        18.35 
TCGA-L5-A4OP TCGA-L5-A4OR TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A8NF TCGA-L5-A8NI 
        7.17         3.16         7.13         7.43         2.66        13.48 
TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-IG-A3YB TCGA-LN-A49L 
       16.47        13.22        46.09        10.36         2.63        10.45 
TCGA-LN-A49Y TCGA-Z6-A8JE 
       12.46         2.10 

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

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

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

$subtype5
TCGA-L5-A4OU TCGA-S8-A6BV TCGA-VR-AA4D TCGA-L5-A88W TCGA-LN-A49S TCGA-LN-A5U5 
       29.00        20.02        46.19        25.12        13.15         4.47 
TCGA-VR-A8EP TCGA-XP-A8T6 
       27.09        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 
   12.84    13.74    12.79    12.66    25.10 
[1] "2.1 - 46.1 (12.8)"  "0.5 - 122.1 (13.7)" "0.3 - 52.6 (12.8)" 
[4] "0.1 - 68.0 (12.7)"  "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 21 11
  subtype5  5  3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   19    4
  subtype2   19    6
  subtype3   21    7
  subtype4   21   11
  subtype5    5    3
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5
  NO        19       19       21       21        5
  YES        4        6        7       11        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 18  7
  subtype5 24 10
subtype1 subtype2 subtype3 subtype4 subtype5 
      23       21       22       25       34 
subtype1 subtype2 subtype3 subtype4 subtype5 
      11        6       10        7       10 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A4QS TCGA-JY-A939 TCGA-L5-A43C 
       25.78        32.45         7.69         3.88        21.70         3.16 
TCGA-L5-A43E TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ 
       30.25         8.94        24.00        32.61        19.99        21.01 
TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OW TCGA-L5-A8NI 
       18.35         7.17         1.38         3.16         7.13        13.48 
TCGA-L5-A8NJ TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-S8-A6BV TCGA-VR-AA4D 
       16.47        46.09        10.36        20.02        46.19 

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

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

$subtype4
TCGA-2H-A9GQ TCGA-L5-A8NL TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A8O2 TCGA-IG-A97H 
        4.21        13.22         0.79        23.41         4.67        14.50 
TCGA-JY-A6FE TCGA-L5-A43H TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R 
        3.68         0.30        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-A9FQ TCGA-LN-A9FR TCGA-VR-A8Q7 
       11.54        12.23        13.18        12.85        12.26        52.27 
TCGA-Z6-A9VB 
        1.32 

$subtype5
TCGA-L5-A4OU TCGA-IC-A6RF TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YB 
       29.00        15.68        33.27        35.21         0.85         2.63 
TCGA-IG-A51D TCGA-IG-A97I TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FG TCGA-L5-A43J 
       17.03        12.16        44.75        68.02        41.52         4.31 
TCGA-L5-A88W TCGA-L5-A8NK TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49S 
       25.12        13.55         5.92        10.45        12.66        13.15 
TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 
       12.46        12.59        12.33        13.22         4.47        12.33 
TCGA-LN-A5U7 TCGA-LN-A7HW TCGA-LN-A9FO TCGA-LN-A9FP TCGA-Q9-A6FU TCGA-S8-A6BW 
       25.25        12.00         0.13        12.03         5.16        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   12.590   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 (12.6)"  "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 14  9
  subtype5 24  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   19    2
  subtype2   15    4
  subtype3   13    8
  subtype4   14    9
  subtype5   24    8
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5
  NO        19       15       13       14       24
  YES        2        4        8        9        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] "subtype2" "subtype5" "subtype5" "subtype5" "subtype3" "subtype5"
 [7] "subtype2" "subtype5" "subtype4" "subtype5" "subtype5" "subtype5"
[13] "subtype4" "subtype4" "subtype4" "subtype4" "subtype5" "subtype4"
[19] "subtype4" "subtype3" "subtype3" "subtype5" "subtype5" "subtype4"
[25] "subtype3" "subtype4" "subtype4" "subtype4" "subtype2" "subtype4"
[31] "subtype5" "subtype5" "subtype5" "subtype5" "subtype5" "subtype5"
[37] "subtype4" "subtype3" "subtype4" "subtype2" "subtype5" "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 40 42
  subtype2 47 21
  subtype3 12 10
  subtype4  7  4
subtype1 subtype2 subtype3 subtype4 
      82       68       22       11 
subtype1 subtype2 subtype3 subtype4 
      42       21       10        4 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GR TCGA-IC-A6RE 
        5.92        13.94         8.94        16.24        32.45         7.69 
TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A939 
        3.88       122.10        60.39        47.38        34.85        21.70 
TCGA-JY-A93C TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43I TCGA-L5-A43M 
       23.18        25.22         3.16        30.25        18.28         8.94 
TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ 
       24.00        26.33         4.70        32.61        19.99        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-A88V TCGA-L5-A88Y 
        4.90        29.00         7.13         7.43         2.60         0.36 
TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NG TCGA-L5-A8NH 
        3.75         3.02        55.50         2.66        35.97        12.92 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR 
       13.48        16.47        13.22         7.76         5.49         8.71 
TCGA-L5-A8NS TCGA-L5-A8NU TCGA-L5-A8NV TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-Q9-A6FW 
       13.41        83.24        52.57        10.36        33.11         7.82 
TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG 
        7.99         7.59         5.06        16.31         7.04        38.40 
TCGA-R6-A6XQ TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WC TCGA-R6-A8WG 
        6.35         9.30        15.78         2.89         2.30        12.69 
TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX 
        7.00        20.02         5.29        16.44         9.27         8.98 
TCGA-VR-A8EQ TCGA-VR-AA4D TCGA-X8-AAAR TCGA-ZR-A9CJ 
       22.82        46.19        18.21        19.73 

$subtype2
TCGA-2H-A9GQ TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A50L TCGA-IG-A51D 
        4.21        33.27        35.21         0.85         0.53        17.03 
TCGA-IG-A5B8 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FD 
        0.79         9.96         4.67        14.50        12.16        68.02 
TCGA-JY-A6FE TCGA-JY-A93F TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88S 
        3.68        24.03         0.30         4.31        47.93        15.48 
TCGA-L5-A88W TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O 
       25.12         5.92        10.45        12.66        12.43        13.41 
TCGA-LN-A49R TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y 
       13.38        15.35        12.59        13.25        12.62        12.46 
TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A8 
       12.59        12.49        12.76        12.59        12.85        15.52 
TCGA-LN-A4A9 TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV 
       11.54        13.22         4.47        12.33        25.25        10.52 
TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8I0 TCGA-LN-A8I1 
       12.00        12.23        12.03        13.18        13.38        13.18 
TCGA-LN-A9FO TCGA-LN-A9FQ TCGA-LN-A9FR TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-A7RC 
        0.13        12.85        12.26         5.16        20.38         3.42 
TCGA-V5-AASV TCGA-VR-A8EO TCGA-VR-A8ER TCGA-VR-A8EU TCGA-VR-A8EY TCGA-VR-A8EZ 
       15.35        25.81        12.43        18.31        33.70        18.18 
TCGA-VR-A8Q7 TCGA-VR-AA4G TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I TCGA-Z6-A8JD 
       52.27        18.05        11.24         9.17        15.91         3.42 
TCGA-Z6-A8JE TCGA-Z6-AAPN 
        2.10         2.66 

$subtype3
TCGA-L5-A88T TCGA-L5-A8NW TCGA-R6-A6Y0 TCGA-IC-A6RF TCGA-IG-A3YC TCGA-IG-A4P3 
       22.82        46.09        53.95        15.68        20.12        18.64 
TCGA-JY-A6FA TCGA-JY-A6FG TCGA-KH-A6WC TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L5-A8NQ 
       44.75        41.52         6.28         7.40        13.55        21.37 
TCGA-L7-A56G TCGA-LN-A49S TCGA-LN-A4MQ TCGA-VR-A8EP TCGA-VR-A8ET TCGA-VR-A8EW 
       10.85        13.15        12.33        27.09         1.55         8.12 
TCGA-VR-A8EX TCGA-XP-A8T6 TCGA-XP-A8T8 TCGA-Z6-A9VB 
       28.11        25.08        14.37         1.32 

$subtype4
TCGA-IG-A7DP TCGA-JY-A93D TCGA-L5-A8NT TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4QT 
       14.86        31.56        27.12        20.78         2.63         9.30 
TCGA-IG-A5S3 TCGA-IG-A625 TCGA-LN-A49P TCGA-LN-A4A5 TCGA-LN-A9FP 
       23.41        12.82        12.33        22.39        12.03 

subtype1 subtype2 subtype3 subtype4 
    0.36     0.13     1.32     2.63 
subtype1 subtype2 subtype3 subtype4 
  122.10    68.02    53.95    31.56 
subtype1 subtype2 subtype3 subtype4 
  13.445   12.590   17.160   14.860 
[1] "0.4 - 122.1 (13.4)" "0.1 - 68.0 (12.6)"  "1.3 - 54.0 (17.2)" 
[4] "2.6 - 31.6 (14.9)" 
D5V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       8        2        1        0         5        16        14
  subtype2       0        1        4        1        32         8        10
  subtype3       0        2        1        0         5         5         2
  subtype4       0        0        0        0         4         2         0
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          4          4          4        2         3
  subtype2          5          2          2        3         0
  subtype3          2          2          0        0         1
  subtype4          3          1          1        0         0
D5V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           8        0        0        0
  STAGE IA          2        1        2        0
  STAGE IB          1        4        1        0
  STAGE II          0        1        0        0
  STAGE IIA         5       32        5        4
  STAGE IIB        16        8        5        2
  STAGE III        14       10        2        0
  STAGE IIIA        4        5        2        3
  STAGE IIIB        4        2        2        1
  STAGE IIIC        4        2        0        1
  STAGE IV          2        3        0        0
  STAGE IVA         3        0        1        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    24  8 36  0
  subtype2     3 24 38  3
  subtype3     5  7  8  0
  subtype4     0  3  6  2
D5V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1       24        3        5        0
  T2           8       24        7        3
  T3          36       38        8        6
  T4           0        3        0        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 21 37  6  4
  subtype2 42 19  3  3
  subtype3  6 12  2  0
  subtype4  7  1  1  1
D5V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       21       42        6        7
  N1       37       19       12        1
  N2        6        3        2        1
  N3        4        3        0        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"
D5V6, binary
          cls
clus        0  1
  subtype1 47  5
  subtype2 59  3
  subtype3 19  1
  subtype4 10  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   47    5
  subtype2   59    3
  subtype3   19    1
  subtype4   10    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       47       59       19       10
  1        5        3        1        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"
D5V7, binary
          cls
clus        0  1
  subtype1 11 71
  subtype2  9 60
  subtype3  3 19
  subtype4  3  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   71
  subtype2    9   60
  subtype3    3   19
  subtype4    3    8
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       11        9        3        3
  MALE         71       60       19        8
[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"
D5V8, binary
          cls
clus        0  1
  subtype1 63  7
  subtype2 41 24
  subtype3 16  5
  subtype4  4  6
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   63    7
  subtype2   41   24
  subtype3   16    5
  subtype4    4    6
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        63       41       16        4
  YES        7       24        5        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"
D5V9, continuous
D5V10, binary
          cls
clus        0  1
  subtype1 82  0
  subtype2  1 68
  subtype3  3 19
  subtype4  3  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   82    0
  subtype2    1   68
  subtype3    3   19
  subtype4    3    8
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA  NOS           82        1        3        3
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0       68       19        8
[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"
D5V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 55  7  0  3
  subtype2 55  4  2  4
  subtype3 18  1  0  0
  subtype4  8  1  0  0
D5V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  R0       55       55       18        8
  R1        7        4        1        1
  R2        0        2        0        0
  RX        3        4        0        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"
D5V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    65
  subtype2    37                         2    27
  subtype3     4                         3    14
  subtype4     4                         0     7
D5V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            1       37        4        4
  BLACK OR AFRICAN AMERICAN        0        2        3        0
  WHITE                           65       27       14        7
[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"
D5V15, binary
          cls
clus        0  1
  subtype1  3 21
  subtype2  0 49
  subtype3  2  9
  subtype4  0  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   21
  subtype2    0   49
  subtype3    2    9
  subtype4    0    9
                        clus
vv                       subtype1 subtype2 subtype3 subtype4
  HISPANIC OR LATINO            3        0        2        0
  NOT HISPANIC OR LATINO       21       49        9        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"

Clustering(6) Variable = MRNASEQ_CHIERARCHICAL
D6V1, survival
          sevent
clus2       0  1
  subtype1 34 34
  subtype2 10 10
  subtype3 62 33
subtype1 subtype2 subtype3 
      68       20       95 
subtype1 subtype2 subtype3 
      34       10       33 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A7DP 
        5.92         8.94        16.24        32.45         7.69        14.86 
TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A939 TCGA-JY-A93C 
      122.10        60.39        47.38        34.85        21.70        23.18 
TCGA-JY-A93D TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43I TCGA-L5-A43M 
       31.56        25.22         3.16        30.25        18.28         8.94 
TCGA-L5-A4OF TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO 
       26.33        32.61        19.99        21.01        18.35         3.32 
TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU 
        7.17         1.38         3.16        58.59         4.90        29.00 
TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NG 
        7.13         7.43         3.75        55.50         2.66        35.97 
TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NN 
       12.92        13.48        16.47        13.22         7.76         5.49 
TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L7-A6VZ TCGA-R6-A6DN 
        8.71        13.41        27.12        83.24        10.36         7.99 
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-2H-A9GM TCGA-IG-A4QS TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A88T TCGA-L5-A88V 
       13.94         3.88        24.00         4.70        22.82         2.60 
TCGA-L5-A88Y TCGA-L5-A893 TCGA-L5-A8NV TCGA-L5-A8NW TCGA-M9-A5M8 TCGA-Q9-A6FW 
        0.36         3.02        52.57        46.09        33.11         7.82 
TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A8W8 TCGA-S8-A6BV 
       16.31         7.04         6.35        53.95         2.89        20.02 
TCGA-V5-A7RB TCGA-X8-AAAR 
        5.29        18.21 

$subtype3
TCGA-2H-A9GQ TCGA-IC-A6RF TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YA 
        4.21        15.68        33.27        35.21         0.85        20.78 
TCGA-IG-A3YB TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A4QT TCGA-IG-A50L TCGA-IG-A51D 
        2.63        20.12        18.64         9.30         0.53        17.03 
TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97H 
        0.79        23.41        12.82         9.96         4.67        14.50 
TCGA-IG-A97I TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-JY-A93F 
       12.16        44.75        68.02         3.68        41.52        24.03 
TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88S TCGA-L5-A88W 
        6.28         0.30         4.31        47.93        15.48        25.12 
TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-L7-A56G TCGA-LN-A49K TCGA-LN-A49L 
        7.40        13.55        21.37        10.85         5.92        10.45 
TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R TCGA-LN-A49S 
       12.66        12.43        13.41        12.33        13.38        13.15 
TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A1 
       15.35        12.59        13.25        12.62        12.46        12.59 
TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 
       12.49        12.76        12.59        22.39        12.85        15.52 
TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 
       11.54        12.33        13.22         4.47        12.33        25.25 
TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8I0 
       10.52        12.00        12.23        12.03        13.18        13.38 
TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FP TCGA-LN-A9FQ TCGA-LN-A9FR TCGA-Q9-A6FU 
       13.18         0.13        12.03        12.85        12.26         5.16 
TCGA-S8-A6BW TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EO TCGA-VR-A8EP TCGA-VR-A8ER 
       20.38         3.42        15.35        25.81        27.09        12.43 
TCGA-VR-A8ET TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8EX TCGA-VR-A8EY TCGA-VR-A8EZ 
        1.55        18.31         8.12        28.11        33.70        18.18 
TCGA-VR-A8Q7 TCGA-VR-AA4G TCGA-VR-AA7B TCGA-VR-AA7D TCGA-VR-AA7I TCGA-XP-A8T6 
       52.27        18.05        11.24         9.17        15.91        25.08 
TCGA-XP-A8T8 TCGA-Z6-A8JD TCGA-Z6-A8JE TCGA-Z6-A9VB TCGA-Z6-AAPN 
       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    12.66 
[1] "1.4 - 122.1 (15.3)" "0.4 - 54.0 (10.9)"  "0.1 - 68.0 (12.7)" 
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 57 33
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   48    9
  subtype2   19    0
  subtype3   57   33
     clus
vv    subtype1 subtype2 subtype3
  NO        48       19       57
  YES        9        0       33
[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] "subtype1" "subtype1" "subtype1" "subtype1" "subtype1" "subtype1"
 [7] "subtype3" "subtype3" "subtype3" "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] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[49] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype3"
[55] "subtype3" "subtype3" "subtype3" "subtype3" "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 41 44
  subtype2 55 31
  subtype3 10  2
subtype1 subtype2 subtype3 
      85       86       12 
subtype1 subtype2 subtype3 
      44       31        2 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GR TCGA-IC-A6RE 
        5.92        13.94         8.94        16.24        32.45         7.69 
TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A939 
        3.88       122.10        60.39        47.38        34.85        21.70 
TCGA-JY-A93C TCGA-JY-A93D TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43I TCGA-L5-A43M 
       23.18        31.56         3.16        30.25        18.28         8.94 
TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ 
       24.00        26.33         4.70        32.61        19.99        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-A88V TCGA-L5-A88Y 
        4.90        29.00         7.13         7.43         2.60         0.36 
TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NG TCGA-L5-A8NH 
        3.75         3.02        55.50         2.66        35.97        12.92 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR 
       13.48        16.47        13.22         7.76         5.49         8.71 
TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L5-A8NV TCGA-L5-A8NW TCGA-L7-A6VZ 
       13.41        27.12        83.24        52.57        46.09        10.36 
TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 
       33.11         7.82         7.99         7.59         5.06        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-S8-A6BV TCGA-V5-A7RB 
        2.89         2.30        12.69         7.00        20.02         5.29 
TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX TCGA-VR-A8EQ TCGA-VR-AA4D TCGA-X8-AAAR 
       16.44         9.27         8.98        22.82        46.19        18.21 
TCGA-ZR-A9CJ 
       19.73 

$subtype2
TCGA-2H-A9GQ TCGA-IC-A6RF TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YC 
        4.21        15.68        33.27        35.21         0.85        20.12 
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-A6FD 
        9.96         4.67        14.50        12.16        44.75        68.02 
TCGA-JY-A6FE TCGA-JY-A6FG TCGA-JY-A93F TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88W 
        3.68        41.52        24.03         4.31        47.93        25.12 
TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-L7-A56G TCGA-LN-A49K TCGA-LN-A49L 
        7.40        13.55        21.37        10.85         5.92        10.45 
TCGA-LN-A49M TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49W 
       12.66        13.41        13.38        13.15        15.35        13.25 
TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 
       12.62        12.46        12.59        12.49        12.76        12.59 
TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR 
       22.39        12.85        15.52        11.54        12.33        13.22 
TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX 
        4.47        12.33        25.25        10.52        12.00        12.23 
TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FQ 
       12.03        13.18        13.38        13.18         0.13        12.85 
TCGA-LN-A9FR TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EO 
       12.26         5.16        20.38         3.42        15.35        25.81 
TCGA-VR-A8EP TCGA-VR-A8ER TCGA-VR-A8ET TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8EX 
       27.09        12.43         1.55        18.31         8.12        28.11 
TCGA-VR-A8EY TCGA-VR-A8EZ TCGA-VR-A8Q7 TCGA-VR-AA4G TCGA-VR-AA7B TCGA-VR-AA7D 
       33.70        18.18        52.27        18.05        11.24         9.17 
TCGA-VR-AA7I TCGA-XP-A8T6 TCGA-XP-A8T7 TCGA-XP-A8T8 TCGA-Z6-A8JD TCGA-Z6-A8JE 
       15.91        25.08        41.23        14.37         3.42         2.10 
TCGA-Z6-A9VB TCGA-Z6-AAPN 
        1.32         2.66 

$subtype3
TCGA-IG-A7DP TCGA-JY-A93E TCGA-L5-A88T TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4QT 
       14.86        25.22        22.82        20.78         2.63         9.30 
TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A88S TCGA-LN-A49N TCGA-LN-A49P TCGA-LN-A9FP 
        6.28         0.30        15.48        12.43        12.33        12.03 

subtype1 subtype2 subtype3 
    0.36     0.13     0.30 
subtype1 subtype2 subtype3 
  122.10    68.02    25.22 
subtype1 subtype2 subtype3 
   13.94    12.85    12.38 
[1] "0.4 - 122.1 (13.9)" "0.1 - 68.0 (12.8)"  "0.3 - 25.2 (12.4)" 
D7V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       8        2        2        0         5        17        14
  subtype2       0        2        3        1        38        12        11
  subtype3       0        1        1        0         3         2         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          3          4          5        2         3
  subtype2          7          5          2        3         1
  subtype3          4          0          0        0         0
D7V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           8        0        0
  STAGE IA          2        2        1
  STAGE IB          2        3        1
  STAGE II          0        1        0
  STAGE IIA         5       38        3
  STAGE IIB        17       12        2
  STAGE III        14       11        1
  STAGE IIIA        3        7        4
  STAGE IIIB        4        5        0
  STAGE IIIC        5        2        0
  STAGE IV          2        3        0
  STAGE IVA         3        1        0
[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    24 10 36  0
  subtype2     7 30 45  3
  subtype3     1  3  6  2
D7V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       24        7        1
  T2          10       30        3
  T3          36       45        6
  T4           0        3        2
[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 22 37  6  5
  subtype2 48 27  6  3
  subtype3  6  5  0  0
D7V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       22       48        6
  N1       37       27        5
  N2        6        6        0
  N3        5        3        0
[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"
D7V6, binary
          cls
clus        0  1
  subtype1 49  5
  subtype2 76  4
  subtype3 10  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   49    5
  subtype2   76    4
  subtype3   10    0
   clus
vv  subtype1 subtype2 subtype3
  0       49       76       10
  1        5        4        0
[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"
D7V7, binary
          cls
clus        0  1
  subtype1 11 74
  subtype2 14 73
  subtype3  2 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   74
  subtype2   14   73
  subtype3    2   10
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       11       14        2
  MALE         74       73       10
[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"
D7V8, binary
          cls
clus        0  1
  subtype1 64  9
  subtype2 54 27
  subtype3  7  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   64    9
  subtype2   54   27
  subtype3    7    5
     clus
vv    subtype1 subtype2 subtype3
  NO        64       54        7
  YES        9       27        5
[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"
D7V9, continuous
D7V10, binary
          cls
clus        0  1
  subtype1 85  0
  subtype2  1 86
  subtype3  3  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   85    0
  subtype2    1   86
  subtype3    3    9
                                   clus
vv                                  subtype1 subtype2 subtype3
  ESOPHAGUS ADENOCARCINOMA  NOS           85        1        3
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0       86        9
[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"
D7V11, continuous
          vv
clus       R0 R1 R2 RX
  subtype1 56  8  0  3
  subtype2 71  4  2  4
  subtype3  9  1  0  0
D7V12, multiclass
    clus
vv   subtype1 subtype2 subtype3
  R0       56       71        9
  R1        8        4        1
  R2        0        2        0
  RX        3        4        0
[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"
D7V13, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    68
  subtype2    41                         5    37
  subtype3     3                         0     9
D7V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1       41        3
  BLACK OR AFRICAN AMERICAN        0        5        0
  WHITE                           68       37        9
[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"
D7V15, binary
          cls
clus        0  1
  subtype1  3 22
  subtype2  3 57
  subtype3  0  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   22
  subtype2    3   57
  subtype3    0    8
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            3        3        0
  NOT HISPANIC OR LATINO       22       57        8
[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(8) Variable = MIRSEQ_CHIERARCHICAL
D8V1, survival
          sevent
clus2       0  1
  subtype1 25 38
  subtype2 19  7
  subtype3 39 22
  subtype4 23 10
subtype1 subtype2 subtype3 subtype4 
      63       26       61       33 
subtype1 subtype2 subtype3 subtype4 
      38        7       22       10 
$subtype1
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-A6FB TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43E TCGA-L5-A43I TCGA-L5-A4OE 
       60.39        47.38        23.18        30.25        18.28        24.00 
TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON 
       26.33         4.70        32.61        19.99        21.01        18.35 
TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OW TCGA-L5-A4OX 
        7.17         1.38         3.16        58.59         7.13         7.43 
TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH 
        2.60         0.36         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         7.99         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-2H-A9GH TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A7DP TCGA-JY-A938 TCGA-JY-A939 
       31.27        32.45         7.69        14.86        34.85        21.70 
TCGA-JY-A93D TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43M TCGA-L5-A4OO TCGA-L5-A4OT 
       31.56        25.22         3.16         8.94         3.32         4.90 
TCGA-L5-A4OU TCGA-L5-A88T TCGA-L5-A893 TCGA-L5-A8NG TCGA-L5-A8NL TCGA-L5-A8NR 
       29.00        22.82         3.02        35.97        13.22         8.71 
TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L5-A8NV TCGA-Q9-A6FW TCGA-R6-A6DQ 
       13.41        27.12        83.24        52.57         7.82         7.59 
TCGA-S8-A6BV TCGA-X8-AAAR 
       20.02        18.21 

$subtype3
TCGA-IC-A6RF TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB 
       15.68        33.27        35.21         0.85        20.78         2.63 
TCGA-IG-A4P3 TCGA-IG-A4QT TCGA-IG-A50L TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS 
       18.64         9.30         0.53        23.41        12.82         9.96 
TCGA-IG-A97H TCGA-IG-A97I TCGA-JY-A6FE TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A43J 
       14.50        12.16         3.68         6.28         0.30         4.31 
TCGA-L5-A88S TCGA-L5-A88Z TCGA-L5-A8NQ TCGA-L7-A56G TCGA-LN-A49K TCGA-LN-A49L 
       15.48         7.40        21.37        10.85         5.92        10.45 
TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R TCGA-LN-A49W TCGA-LN-A49X 
       12.43        13.41        12.33        13.38        13.25        12.62 
TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4MQ 
       12.59        12.49        12.59        22.39        12.85        12.33 
TCGA-LN-A4MR TCGA-LN-A5U5 TCGA-LN-A5U6 TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-LN-A8I0 
       13.22         4.47        12.33        12.03        13.18        13.38 
TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FP TCGA-LN-A9FQ TCGA-LN-A9FR TCGA-Q9-A6FU 
       13.18         0.13        12.03        12.85        12.26         5.16 
TCGA-S8-A6BW TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EP TCGA-VR-A8ER TCGA-VR-A8ET 
       20.38         3.42        15.35        27.09        12.43         1.55 
TCGA-VR-A8EW TCGA-VR-A8EZ TCGA-VR-AA4G TCGA-VR-AA7D TCGA-VR-AA7I TCGA-XP-A8T8 
        8.12        18.18        18.05         9.17        15.91        14.37 
TCGA-Z6-A9VB 
        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   12.490   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 35 23
  subtype4 22  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   49    6
  subtype2   19    3
  subtype3   35   23
  subtype4   22    9
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        49       19       35       22
  YES        6        3       23        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] "subtype1" "subtype1" "subtype1" "subtype1" "subtype1" "subtype1"
 [7] "subtype3" "subtype3" "subtype3" "subtype3" "subtype3" "subtype4"
[13] "subtype4" "subtype3" "subtype3" "subtype3" "subtype3" "subtype4"
[19] "subtype3" "subtype3" "subtype3" "subtype3" "subtype4" "subtype4"
[25] "subtype3" "subtype3" "subtype4" "subtype3" "subtype3" "subtype4"
[31] "subtype3" "subtype3" "subtype3" "subtype4" "subtype4" "subtype3"
[37] "subtype3" "subtype3" "subtype3" "subtype4" "subtype4" "subtype4"
[43] "subtype4" "subtype3" "subtype3" "subtype3" "subtype3" "subtype4"
[49] "subtype3" "subtype3" "subtype3" "subtype4" "subtype3" "subtype4"
[55] "subtype4" "subtype3" "subtype4" "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 31 36
  subtype2 40 25
  subtype3 24 11
  subtype4  6  5
subtype1 subtype2 subtype3 subtype4 
      67       65       35       11 
subtype1 subtype2 subtype3 subtype4 
      36       25       11        5 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-IG-A4QS TCGA-JY-A6F8 
        5.92        13.94         8.94        16.24         3.88       122.10 
TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A93C TCGA-L5-A43C TCGA-L5-A43E 
       60.39        47.38        34.85        23.18         3.16        30.25 
TCGA-L5-A43I TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI 
       18.28         8.94        24.00         4.70        32.61        19.99 
TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT 
       18.35         7.17         1.38         3.16        58.59         4.90 
TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 
       29.00         7.13         7.43         2.60         0.36         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-A6KZ TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ 
        7.99         7.59         5.06        16.31        38.40         6.35 
TCGA-R6-A6Y0 TCGA-R6-A8W5 TCGA-R6-A8W8 TCGA-R6-A8WG TCGA-RE-A7BO TCGA-S8-A6BV 
       53.95        15.78         2.89        12.69         7.00        20.02 
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 
       18.21 

$subtype2
TCGA-2H-A9GQ TCGA-IC-A6RF TCGA-IG-A3QL TCGA-IG-A4P3 TCGA-IG-A51D TCGA-IG-A5B8 
        4.21        15.68        35.21        18.64        17.03         0.79 
TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97H TCGA-JY-A6FA 
       23.41        12.82         9.96         4.67        14.50        44.75 
TCGA-JY-A6FE TCGA-JY-A6FG TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A88Z 
        3.68        41.52         4.31        47.93        25.12         7.40 
TCGA-L7-A56G TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49O TCGA-LN-A49R 
       10.85         5.92        10.45        12.66        13.41        13.38 
TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4A2 TCGA-LN-A4A4 
       13.15        15.35        12.46        12.59        12.49        12.59 
TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U5 
       12.85        15.52        11.54        12.33        13.22         4.47 
TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW TCGA-LN-A7HX TCGA-LN-A7HY 
       12.33        25.25        10.52        12.00        12.23        12.03 
TCGA-LN-A7HZ TCGA-LN-A8I0 TCGA-LN-A8I1 TCGA-LN-A9FO TCGA-LN-A9FQ TCGA-Q9-A6FU 
       13.18        13.38        13.18         0.13        12.85         5.16 
TCGA-S8-A6BW TCGA-V5-A7RC TCGA-VR-A8EO TCGA-VR-A8EP TCGA-VR-A8ER TCGA-VR-A8EU 
       20.38         3.42        25.81        27.09        12.43        18.31 
TCGA-VR-A8EW TCGA-VR-A8EX TCGA-VR-A8EY TCGA-VR-A8EZ TCGA-VR-A8Q7 TCGA-VR-AA7B 
        8.12        28.11        33.70        18.18        52.27        11.24 
TCGA-VR-AA7D TCGA-XP-A8T7 TCGA-XP-A8T8 TCGA-Z6-A9VB TCGA-Z6-AAPN 
        9.17        41.23        14.37         1.32         2.66 

$subtype3
TCGA-2H-A9GR TCGA-IC-A6RE TCGA-IG-A7DP TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E 
       32.45         7.69        14.86        21.70        31.56        25.22 
TCGA-L5-A4OF TCGA-L5-A4OO TCGA-L5-A88T TCGA-L5-A8NG TCGA-L5-A8NS TCGA-L5-A8NT 
       26.33         3.32        22.82        35.97        13.41        27.12 
TCGA-L5-A8NU TCGA-L5-A8NV TCGA-Q9-A6FW TCGA-IG-A3I8 TCGA-IG-A3YA TCGA-IG-A3YB 
       83.24        52.57         7.82        33.27        20.78         2.63 
TCGA-IG-A3YC TCGA-IG-A4QT TCGA-IG-A50L TCGA-IG-A97I TCGA-KH-A6WC TCGA-L5-A43H 
       20.12         9.30         0.53        12.16         6.28         0.30 
TCGA-L5-A88S TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-LN-A49N TCGA-LN-A49P TCGA-LN-A49W 
       15.48        13.55        21.37        12.43        12.33        13.25 
TCGA-LN-A49X TCGA-LN-A4A5 TCGA-LN-A9FP TCGA-VR-AA7I TCGA-XP-A8T6 
       12.62        22.39        12.03        15.91        25.08 

$subtype4
TCGA-L5-A8NL TCGA-R6-A6L6 TCGA-R6-A6Y2 TCGA-ZR-A9CJ TCGA-IG-A3Y9 TCGA-JY-A6FD 
       13.22         7.04         9.30        19.73         0.85        68.02 
TCGA-LN-A9FR TCGA-VR-A8ET TCGA-VR-AA4G TCGA-Z6-A8JD TCGA-Z6-A8JE 
       12.26         1.55        18.05         3.42         2.10 

subtype1 subtype2 subtype3 subtype4 
    0.36     0.13     0.30     0.85 
subtype1 subtype2 subtype3 subtype4 
  122.10    52.27    83.24    68.02 
subtype1 subtype2 subtype3 subtype4 
   13.48    12.82    15.48     9.30 
[1] "0.4 - 122.1 (13.5)" "0.1 - 52.3 (12.8)"  "0.3 - 83.2 (15.5)" 
[4] "0.8 - 68.0 (9.3)"  
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        30         8         8
  subtype3       0        1        1        0        12         8         4
  subtype4       0        0        0        0         2         2         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          3          3          2        2         3
  subtype2          2          5          2        3         1
  subtype3          6          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       30       12        2
  STAGE IIB        12        8        8        2
  STAGE III        12        8        4        1
  STAGE IIIA        3        2        6        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 34  1
  subtype3     4  9 19  3
  subtype4     0  3  5  1
D9V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1       20        7        4        0
  T2           8       22        9        3
  T3          27       34       19        5
  T4           0        1        3        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"
          vv
clus       N0 N1 N2 N3
  subtype1 16 32  5  2
  subtype2 35 20  5  3
  subtype3 18 13  1  2
  subtype4  4  3  1  1
D9V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       16       35       18        4
  N1       32       20       13        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 56  4
  subtype3 32  0
  subtype4  8  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   36    5
  subtype2   56    4
  subtype3   32    0
  subtype4    8    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       36       56       32        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 57
  subtype2  9 57
  subtype3  4 31
  subtype4  2  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10   57
  subtype2    9   57
  subtype3    4   31
  subtype4    2    9
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       10        9        4        2
  MALE         57       57       31        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"
D9V8, binary
          cls
clus        0  1
  subtype1 53  6
  subtype2 41 21
  subtype3 20 11
  subtype4  9  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   53    6
  subtype2   41   21
  subtype3   20   11
  subtype4    9    1
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        53       41       20        9
  YES        6       21       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 67  0
  subtype2  1 65
  subtype3 15 20
  subtype4  4  7
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   67    0
  subtype2    1   65
  subtype3   15   20
  subtype4    4    7
                                   clus
vv                                  subtype1 subtype2 subtype3 subtype4
  ESOPHAGUS ADENOCARCINOMA  NOS           67        1       15        4
  ESOPHAGUS SQUAMOUS CELL CARCINOMA        0       65       20        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 45  6  0  2
  subtype2 55  2  1  3
  subtype3 24  5  1  1
  subtype4  8  0  0  1
D9V12, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  R0       45       55       24        8
  R1        6        2        5        0
  R2        0        1        1        0
  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    51
  subtype2    34                         3    25
  subtype3     7                         1    26
  subtype4     2                         0     9
D9V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            1       34        7        2
  BLACK OR AFRICAN AMERICAN        0        3        1        0
  WHITE                           51       25       26        9
[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 17
  subtype2  2 45
  subtype3  1 16
  subtype4  1  6
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   17
  subtype2    2   45
  subtype3    1   16
  subtype4    1    6
                        clus
vv                       subtype1 subtype2 subtype3 subtype4
  HISPANIC OR LATINO            2        2        1        1
  NOT HISPANIC OR LATINO       17       45       16        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 24 39
  subtype2 16  6
  subtype3 61 32
subtype1 subtype2 subtype3 
      63       22       93 
subtype1 subtype2 subtype3 
      39        6       32 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GQ TCGA-IG-A4QS 
        5.92        13.94         8.94        16.24         4.21         3.88 
TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43E TCGA-L5-A43I 
      122.10        60.39        47.38        23.18        30.25        18.28 
TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4ON 
       24.00        26.33         4.70        32.61        19.99        18.35 
TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OW TCGA-L5-A4OX 
        7.17         1.38         3.16        58.59         7.13         7.43 
TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH 
        2.60         0.36         3.75        55.50         2.66        12.92 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NW 
       13.48        16.47         7.76         5.49         8.71        46.09 
TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 
       10.36        33.11         7.99         5.06        16.31         7.04 
TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-R6-A8W5 TCGA-R6-A8W8 
       38.40         6.35        53.95         9.30        15.78         2.89 
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-2H-A9GR TCGA-IC-A6RE TCGA-JY-A938 TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E 
       32.45         7.69        34.85        21.70        31.56        25.22 
TCGA-L5-A43C TCGA-L5-A43M TCGA-L5-A4OO TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A893 
        3.16         8.94         3.32         4.90        29.00         3.02 
TCGA-L5-A8NG TCGA-L5-A8NL TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L5-A8NV 
       35.97        13.22        13.41        27.12        83.24        52.57 
TCGA-Q9-A6FW TCGA-R6-A6DQ TCGA-S8-A6BV TCGA-X8-AAAR 
        7.82         7.59        20.02        18.21 

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

subtype1 subtype2 subtype3 
    0.36     3.02     0.13 
subtype1 subtype2 subtype3 
  122.10    83.24    68.02 
subtype1 subtype2 subtype3 
  13.480   19.115   12.820 
[1] "0.4 - 122.1 (13.5)" "3.0 - 83.2 (19.1)"  "0.1 - 68.0 (12.8)" 
D10V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       6        2        2        0         1        12        13
  subtype2       1        0        0        0         4         5         2
  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           6        1        0
  STAGE IA          2        0        3
  STAGE IB          2        0        3
  STAGE II          0        0        1
  STAGE IIA         1        4       41
  STAGE IIB        12        5       13
  STAGE III        13        2       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    19  8 24  0
  subtype2     4  2 14  0
  subtype3     8 32 47  5
D10V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       19        4        8
  T2           8        2       32
  T3          24       14       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 13 31  4  3
  subtype2  8  8  2  2
  subtype3 52 29  6  3
D10V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       13        8       52
  N1       31        8       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 34  4
  subtype2 16  1
  subtype3 82  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   34    4
  subtype2   16    1
  subtype3   82    4
   clus
vv  subtype1 subtype2 subtype3
  0       34       16       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  7 56
  subtype2  3 19
  subtype3 15 79
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7   56
  subtype2    3   19
  subtype3   15   79
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        7        3       15
  MALE         56       19       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 50  6
  subtype2 15  3
  subtype3 58 30
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   50    6
  subtype2   15    3
  subtype3   58   30
     clus
vv    subtype1 subtype2 subtype3
  NO        50       15       58
  YES        6        3       30
[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 63  0
  subtype2 22  0
  subtype3  2 92
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   63    0
  subtype2   22    0
  subtype3    2   92
                                   clus
vv                                  subtype1 subtype2 subtype3
  ESOPHAGUS ADENOCARCINOMA  NOS           63       22        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 42  5  0  1
  subtype2 15  3  0  2
  subtype3 75  5  2  4
D10V12, multiclass
    clus
vv   subtype1 subtype2 subtype3
  R0       42       15       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    47
  subtype2     0                         0    20
  subtype3    43                         4    44
D10V14, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        0       43
  BLACK OR AFRICAN AMERICAN        0        0        4
  WHITE                           47       20       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 16
  subtype2  0  5
  subtype3  3 63
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   16
  subtype2    0    5
  subtype3    3   63
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            3        0        3
  NOT HISPANIC OR LATINO       16        5       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"
