[1] "ofn"       "-oTUVM-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/UVM-TP/22507229/UVM-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/UVM-TP/22542449/UVM-TP.mergedcluster.txt"

nPatients in clinical file=80, in cluster file=80, common to both=80
[1]  8 80
[1] "CN_CNMF"
[1] 3
 1  2  3  4  5  6 
22  7 10 31  6  4 
 1  2  3  4  5  6 
22  7 10 31  6  4 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3  4 
28 14 14 24 
 1  2  3  4 
28 14 14 24 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2  3  4 
18 15 32 15 
 1  2  3  4 
18 15 32 15 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
 1  2  3 
29 33 18 
 1  2  3 
29 33 18 
[1] "MIRSEQ_CNMF"
[1] 3
 1  2  3  4  5  6 
 8  8 11 25 23  5 
 1  2  3  4  5  6 
 8  8 11 25 23  5 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
 1  2  3  4 
17 13 28 22 
 1  2  3  4 
17 13 28 22 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
 1  2  3  4  5  6  7 
20  7 17  9  8  7  6 
 1  2  3  4  5  6  7 
20  7 17  9  8  7  6 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
 1  2  3  4 
18 28 16 12 
 1  2  3  4 
18 28 16 12 
[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] "RACE"                                
[14] "ETHNICITY"                           

Input Data has 14 rows and 80 columns.

[1] "Last Follow UP"
Variable 1:'YEARS_TO_BIRTH':	nDistinctValues=40,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 2:'VITAL_STATUS':	nDistinctValues=2,	numeric=TRUE,	binary=TRUE,	exclude=FALSE.
Variable 3:'DAYS_TO_DEATH':	nDistinctValues=23,	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=56,	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=6,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 7:'PATHOLOGY_T_STAGE':	nDistinctValues=11,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 8:'PATHOLOGY_N_STAGE':	nDistinctValues=2,	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=6,	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:'RACE':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "RACE is excluded in the analysis because there is no more than two cases of (unique non-NA values)"
Variable 14:'ETHNICITY':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "ETHNICITY excluded in the analysis because there is no case of (both >= 3) in the table below"
              HISPANIC OR LATINO NOT HISPANIC OR LATINO
freq.values   "1"                "52"                  
freq.contrast "52"               "1"                   
both >= 3     "FALSE"            "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 80 columns, 1 survival variables, and 6 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"  "PATHOLOGY_T_STAGE"
[4] "PATHOLOGY_M_STAGE" "GENDER"            "RADIATION_THERAPY"
YEARS_TO_BIRTH, nv=40, binary=FALSE, numeric=TRUE
PATHOLOGIC_STAGE, nv=6, binary=FALSE, numeric=FALSE
PATHOLOGY_T_STAGE, nv=3, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.T',vnm)"
vv
T2 T3 T4 
14 32 34 
[1] "table(vv)"
vv
T2 T3 T4 
14 32 34 
$ClinVariableName
[1] "PATHOLOGY_T_STAGE"

$Table
vv
T2 T3 T4 
14 32 34 

$nClasses
[1] 3

$ClinVariableType
[1] "multiclass(3)"


T2 T3 T4 
14 32 34 
PATHOLOGY_M_STAGE, nv=2, binary=FALSE, numeric=TRUE
GENDER, nv=2, binary=FALSE, numeric=FALSE
RADIATION_THERAPY, nv=2, binary=FALSE, numeric=FALSE

Clustering(1) Variable = CN_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 15  7
  subtype2  3  4
  subtype3  4  6
  subtype4 29  2
  subtype5  4  2
  subtype6  2  2
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
      22        7       10       31        6        4 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
       7        4        6        2        2        2 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9EF TCGA-V4-A9EM TCGA-V4-A9EO 
        4.90        15.09        82.16        38.30        31.76        25.41 
TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EV TCGA-V4-A9F1 TCGA-V4-A9F2 TCGA-VD-A8K8 
       14.96        49.68        41.72        30.84        24.13        45.27 
TCGA-VD-A8KD TCGA-VD-A8KE TCGA-VD-A8KF TCGA-VD-A8KK TCGA-VD-A8KM TCGA-VD-AA8P 
        3.75        26.99         1.32         2.10         0.13         2.83 
TCGA-WC-A882 TCGA-WC-A888 TCGA-YZ-A980 TCGA-YZ-A985 
       36.56        18.90        61.22        38.93 

$subtype2
TCGA-V3-A9ZX TCGA-V4-A9E7 TCGA-V4-A9EI TCGA-V4-A9EU TCGA-V4-A9EX TCGA-V4-A9F5 
       15.45        13.64        12.79        23.31        24.00         6.67 
TCGA-WC-A88A 
        2.70 

$subtype3
TCGA-WC-AA9A TCGA-V4-A9E8 TCGA-V4-A9EE TCGA-V4-A9F0 TCGA-V4-A9F8 TCGA-VD-A8KL 
       14.89        26.56        13.08        31.07        19.63        20.98 
TCGA-VD-AA8O TCGA-VD-AA8S TCGA-YZ-A982 TCGA-YZ-A984 
       19.92        14.04        16.27        45.90 

$subtype4
TCGA-WC-A87U TCGA-WC-A881 TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EH 
       51.98        35.01        40.96        44.32        24.43        22.03 
TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9EY TCGA-V4-A9EZ 
       24.53        33.80        44.78        39.81        27.52        19.69 
TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 TCGA-VD-A8KA TCGA-VD-A8KB 
       20.84        41.29        47.97        46.82        38.73        44.52 
TCGA-VD-A8KG TCGA-VD-A8KJ TCGA-VD-A8KO TCGA-VD-AA8M TCGA-VD-AA8Q TCGA-VD-AA8R 
        0.62        37.81        26.14         0.20        20.91         0.20 
TCGA-WC-A87T TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A884 TCGA-WC-A885 TCGA-WC-AA9E 
       85.48        55.99        41.36         0.39        22.55        27.55 
TCGA-YZ-A983 
       26.24 

$subtype5
TCGA-V4-A9EL TCGA-V4-A9ED TCGA-V4-A9F3 TCGA-VD-A8KI TCGA-VD-A8KN TCGA-VD-AA8N 
       32.28        35.44        28.70        36.59         2.24         1.45 

$subtype6
TCGA-VD-A8KH TCGA-VD-AA8T TCGA-WC-A87Y TCGA-WC-A883 
       38.07         1.61        43.20         7.92 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
    0.13     2.70    13.08     0.20     1.45     1.61 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
   82.16    24.00    45.90    85.48    36.59    43.20 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
  26.200   13.640   19.775   33.800   30.490   22.995 
[1] "0.1 - 82.2 (26.2)"  "2.7 - 24.0 (13.6)"  "13.1 - 45.9 (19.8)"
[4] "0.2 - 85.5 (33.8)"  "1.4 - 36.6 (30.5)"  "1.6 - 43.2 (23.0)" 
D1V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1         7          9          3          0        2
  subtype2         0         1          2          1          1        2
  subtype3         2         4          2          2          0        0
  subtype4         7        13          8          3          0        0
  subtype5         1         2          3          0          0        0
  subtype6         1         0          1          1          0        0
D1V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  STAGE IIA         1        0        2        7        1        1
  STAGE IIB         7        1        4       13        2        0
  STAGE IIIA        9        2        2        8        3        1
  STAGE IIIB        3        1        2        3        0        1
  STAGE IIIC        0        1        0        0        0        0
  STAGE IV          2        2        0        0        0        0
[1] 6 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T2 T3 T4
  subtype1  2  9 11
  subtype2  1  0  6
  subtype3  2  4  4
  subtype4  7 14 10
  subtype5  1  3  2
  subtype6  1  2  1
D1V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  T2        2        1        2        7        1        1
  T3        9        0        4       14        3        2
  T4       11        6        4       10        2        1
[1] 3 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V5, binary
          cls
clus        0  1
  subtype1 12  2
  subtype2  4  2
  subtype3  6  0
  subtype4 22  0
  subtype5  4  0
  subtype6  3  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   12    2
  subtype2    4    2
  subtype3    6    0
  subtype4   22    0
  subtype5    4    0
  subtype6    3    0
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  0       12        4        6       22        4        3
  1        2        2        0        0        0        0
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V6, binary
          cls
clus        0  1
  subtype1 11 11
  subtype2  3  4
  subtype3  4  6
  subtype4 13 18
  subtype5  2  4
  subtype6  2  2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   11
  subtype2    3    4
  subtype3    4    6
  subtype4   13   18
  subtype5    2    4
  subtype6    2    2
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  FEMALE       11        3        4       13        2        2
  MALE         11        4        6       18        4        2
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V7, binary
          cls
clus        0  1
  subtype1 21  0
  subtype2  6  1
  subtype3 10  0
  subtype4 30  1
  subtype5  6  0
  subtype6  3  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   21    0
  subtype2    6    1
  subtype3   10    0
  subtype4   30    1
  subtype5    6    0
  subtype6    3    1
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  NO        21        6       10       30        6        3
  YES        0        1        0        1        0        1
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(2) Variable = METHLYATION_CNMF
D2V1, survival
          sevent
clus2       0  1
  subtype1 11 17
  subtype2 13  1
  subtype3 11  3
  subtype4 22  2
subtype1 subtype2 subtype3 subtype4 
      28       14       14       24 
subtype1 subtype2 subtype3 subtype4 
      17        1        3        2 
$subtype1
TCGA-V4-A9EL TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9E7 TCGA-V4-A9EE TCGA-V4-A9EF 
       32.28         4.90        15.45        13.64        13.08        38.30 
TCGA-V4-A9EI TCGA-V4-A9EQ TCGA-V4-A9EU TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F0 
       12.79        14.96        23.31        41.72        24.00        31.07 
TCGA-V4-A9F1 TCGA-V4-A9F3 TCGA-V4-A9F5 TCGA-V4-A9F8 TCGA-VD-A8K8 TCGA-VD-A8KD 
       30.84        28.70         6.67        19.63        45.27         3.75 
TCGA-VD-A8KI TCGA-VD-A8KL TCGA-VD-A8KM TCGA-VD-A8KN TCGA-VD-AA8N TCGA-VD-AA8O 
       36.59        20.98         0.13         2.24         1.45        19.92 
TCGA-WC-A87Y TCGA-WC-A883 TCGA-WC-A888 TCGA-WC-A88A 
       43.20         7.92        18.90         2.70 

$subtype2
TCGA-WC-A87U TCGA-V3-A9ZY TCGA-V4-A9EH TCGA-V4-A9EM TCGA-V4-A9EW TCGA-V4-A9EY 
       51.98        15.09        22.03        31.76        39.81        27.52 
TCGA-VD-A8K7 TCGA-VD-A8KE TCGA-VD-A8KH TCGA-VD-A8KO TCGA-VD-AA8R TCGA-WC-A87T 
       47.97        26.99        38.07        26.14         0.20        85.48 
TCGA-WC-A882 TCGA-YZ-A980 
       36.56        61.22 

$subtype3
TCGA-WC-AA9A TCGA-V4-A9E5 TCGA-V4-A9ED TCGA-V4-A9EO TCGA-V4-A9ES TCGA-V4-A9EZ 
       14.89        82.16        35.44        25.41        49.68        19.69 
TCGA-V4-A9F2 TCGA-VD-A8KF TCGA-VD-A8KK TCGA-VD-AA8P TCGA-VD-AA8T TCGA-WC-A87W 
       24.13         1.32         2.10         2.83         1.61        55.99 
TCGA-YZ-A984 TCGA-YZ-A985 
       45.90        38.93 

$subtype4
TCGA-WC-A881 TCGA-V4-A9E8 TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EJ 
       35.01        26.56        40.96        44.32        24.43        24.53 
TCGA-V4-A9EK TCGA-V4-A9ET TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K9 TCGA-VD-A8KA 
       33.80        44.78        20.84        41.29        46.82        38.73 
TCGA-VD-A8KB TCGA-VD-A8KG TCGA-VD-A8KJ TCGA-VD-AA8M TCGA-VD-AA8Q TCGA-VD-AA8S 
       44.52         0.62        37.81         0.20        20.91        14.04 
TCGA-WC-A880 TCGA-WC-A884 TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A982 TCGA-YZ-A983 
       41.36         0.39        22.55        27.55        16.27        26.24 

subtype1 subtype2 subtype3 subtype4 
    0.13     0.20     1.32     0.20 
subtype1 subtype2 subtype3 subtype4 
   45.27    85.48    82.16    46.82 
subtype1 subtype2 subtype3 subtype4 
  19.265   34.160   24.770   27.055 
[1] "0.1 - 45.3 (19.3)" "0.2 - 85.5 (34.2)" "1.3 - 82.2 (24.8)"
[4] "0.2 - 46.8 (27.1)"
D2V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1        10          8          3          1        4
  subtype2         2         4          6          2          0        0
  subtype3         3         3          6          2          0        0
  subtype4         6        10          5          3          0        0
D2V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE IIA         1        2        3        6
  STAGE IIB        10        4        3       10
  STAGE IIIA        8        6        6        5
  STAGE IIIB        3        2        2        3
  STAGE IIIC        1        0        0        0
  STAGE IV          4        0        0        0
[1] 6 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       T2 T3 T4
  subtype1  2 11 15
  subtype2  3  5  6
  subtype3  3  6  5
  subtype4  6 10  8
D2V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  T2        2        3        3        6
  T3       11        5        6       10
  T4       15        6        5        8
[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"
D2V5, binary
          cls
clus        0  1
  subtype1 18  4
  subtype2  8  0
  subtype3  9  0
  subtype4 16  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   18    4
  subtype2    8    0
  subtype3    9    0
  subtype4   16    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       18        8        9       16
  1        4        0        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"
D2V6, binary
          cls
clus        0  1
  subtype1 11 17
  subtype2  5  9
  subtype3 10  4
  subtype4  9 15
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   17
  subtype2    5    9
  subtype3   10    4
  subtype4    9   15
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       11        5       10        9
  MALE         17        9        4       15
[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"
D2V7, binary
          cls
clus        0  1
  subtype1 25  2
  subtype2 14  0
  subtype3 14  0
  subtype4 23  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   25    2
  subtype2   14    0
  subtype3   14    0
  subtype4   23    1
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        25       14       14       23
  YES        2        0        0        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"

Clustering(3) Variable = MRNASEQ_CNMF
D3V1, survival
          sevent
clus2       0  1
  subtype1  9  9
  subtype2 10  5
  subtype3 31  1
  subtype4  7  8
subtype1 subtype2 subtype3 subtype4 
      18       15       32       15 
subtype1 subtype2 subtype3 subtype4 
       9        5        1        8 
$subtype1
TCGA-WC-AA9A TCGA-RZ-AB0B TCGA-V4-A9E7 TCGA-V4-A9EE TCGA-V4-A9EF TCGA-V4-A9EI 
       14.89         4.90        13.64        13.08        38.30        12.79 
TCGA-V4-A9EO TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EU TCGA-V4-A9EX TCGA-V4-A9F1 
       25.41        14.96        49.68        23.31        24.00        30.84 
TCGA-V4-A9F5 TCGA-V4-A9F8 TCGA-VD-A8KF TCGA-VD-AA8T TCGA-WC-A88A TCGA-YZ-A985 
        6.67        19.63         1.32         1.61         2.70        38.93 

$subtype2
TCGA-V3-A9ZX TCGA-V4-A9ED TCGA-V4-A9EM TCGA-V4-A9EY TCGA-V4-A9F0 TCGA-VD-A8KL 
       15.45        35.44        31.76        27.52        31.07        20.98 
TCGA-VD-AA8P TCGA-VD-AA8Q TCGA-WC-A87Y TCGA-WC-A882 TCGA-WC-A883 TCGA-WC-A884 
        2.83        20.91        43.20        36.56         7.92         0.39 
TCGA-YZ-A980 TCGA-YZ-A982 TCGA-YZ-A984 
       61.22        16.27        45.90 

$subtype3
TCGA-WC-A87U TCGA-WC-A881 TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9E9 TCGA-V4-A9EA 
       51.98        35.01        15.09        82.16        40.96        44.32 
TCGA-V4-A9EC TCGA-V4-A9EJ TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9EZ TCGA-V4-A9F2 
       24.43        24.53        44.78        39.81        19.69        24.13 
TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 TCGA-VD-A8KA TCGA-VD-A8KB 
       20.84        41.29        47.97        46.82        38.73        44.52 
TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KH TCGA-VD-A8KJ TCGA-VD-A8KO TCGA-VD-AA8M 
       26.99         0.62        38.07        37.81        26.14         0.20 
TCGA-VD-AA8R TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A885 
        0.20        14.04        85.48        55.99        41.36        22.55 
TCGA-WC-AA9E TCGA-YZ-A983 
       27.55        26.24 

$subtype4
TCGA-V4-A9EL TCGA-V4-A9E8 TCGA-V4-A9EH TCGA-V4-A9EK TCGA-V4-A9EV TCGA-V4-A9F3 
       32.28        26.56        22.03        33.80        41.72        28.70 
TCGA-VD-A8K8 TCGA-VD-A8KD TCGA-VD-A8KI TCGA-VD-A8KK TCGA-VD-A8KM TCGA-VD-A8KN 
       45.27         3.75        36.59         2.10         0.13         2.24 
TCGA-VD-AA8N TCGA-VD-AA8O TCGA-WC-A888 
        1.45        19.92        18.90 

subtype1 subtype2 subtype3 subtype4 
    1.32     0.39     0.20     0.13 
subtype1 subtype2 subtype3 subtype4 
   49.68    61.22    85.48    45.27 
subtype1 subtype2 subtype3 subtype4 
  14.925   27.520   36.410   22.030 
[1] "1.3 - 49.7 (14.9)" "0.4 - 61.2 (27.5)" "0.2 - 85.5 (36.4)"
[4] "0.1 - 45.3 (22.0)"
D3V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         2         2          7          3          1        3
  subtype2         0         6          5          3          0        0
  subtype3         9        12          8          3          0        0
  subtype4         1         7          5          1          0        1
D3V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE IIA         2        0        9        1
  STAGE IIB         2        6       12        7
  STAGE IIIA        7        5        8        5
  STAGE IIIB        3        3        3        1
  STAGE IIIC        1        0        0        0
  STAGE IV          3        0        0        1
[1] 6 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       T2 T3 T4
  subtype1  2  3 13
  subtype2  2  8  5
  subtype3  9 14  9
  subtype4  1  7  7
D3V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  T2        2        2        9        1
  T3        3        8       14        7
  T4       13        5        9        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"
D3V5, binary
          cls
clus        0  1
  subtype1 12  3
  subtype2 10  0
  subtype3 20  0
  subtype4  9  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   12    3
  subtype2   10    0
  subtype3   20    0
  subtype4    9    1
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       12       10       20        9
  1        3        0        0        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"
D3V6, binary
          cls
clus        0  1
  subtype1  9  9
  subtype2  8  7
  subtype3 13 19
  subtype4  5 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9    9
  subtype2    8    7
  subtype3   13   19
  subtype4    5   10
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        9        8       13        5
  MALE          9        7       19       10
[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"
D3V7, binary
          cls
clus        0  1
  subtype1 16  1
  subtype2 14  1
  subtype3 31  1
  subtype4 15  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   16    1
  subtype2   14    1
  subtype3   31    1
  subtype4   15    0
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        16       14       31       15
  YES        1        1        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"

Clustering(4) Variable = MRNASEQ_CHIERARCHICAL
D4V1, survival
          sevent
clus2       0  1
  subtype1 12 17
  subtype2 32  1
  subtype3 13  5
subtype1 subtype2 subtype3 
      29       33       18 
subtype1 subtype2 subtype3 
      17        1        5 
$subtype1
TCGA-V4-A9EL TCGA-WC-AA9A TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9E7 TCGA-V4-A9E8 
       32.28        14.89         4.90        15.45        13.64        26.56 
TCGA-V4-A9EE TCGA-V4-A9EF TCGA-V4-A9EI TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EU 
       13.08        38.30        12.79        14.96        49.68        23.31 
TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F1 TCGA-V4-A9F3 TCGA-V4-A9F5 TCGA-V4-A9F8 
       41.72        24.00        30.84        28.70         6.67        19.63 
TCGA-VD-A8K8 TCGA-VD-A8KD TCGA-VD-A8KF TCGA-VD-A8KI TCGA-VD-A8KM TCGA-VD-A8KN 
       45.27         3.75         1.32        36.59         0.13         2.24 
TCGA-VD-AA8N TCGA-VD-AA8O TCGA-VD-AA8T TCGA-WC-A888 TCGA-WC-A88A 
        1.45        19.92         1.61        18.90         2.70 

$subtype2
TCGA-WC-A87U TCGA-WC-A881 TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9E9 TCGA-V4-A9EA 
       51.98        35.01        15.09        82.16        40.96        44.32 
TCGA-V4-A9EC TCGA-V4-A9EH TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9ET TCGA-V4-A9EW 
       24.43        22.03        24.53        33.80        44.78        39.81 
TCGA-V4-A9EZ TCGA-V4-A9F2 TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 
       19.69        24.13        20.84        41.29        47.97        46.82 
TCGA-VD-A8KA TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KJ TCGA-VD-A8KO 
       38.73        44.52        26.99         0.62        37.81        26.14 
TCGA-VD-AA8M TCGA-VD-AA8R TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A87W TCGA-WC-A880 
        0.20         0.20        14.04        85.48        55.99        41.36 
TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A983 
       22.55        27.55        26.24 

$subtype3
TCGA-V4-A9ED TCGA-V4-A9EM TCGA-V4-A9EO TCGA-V4-A9EY TCGA-V4-A9F0 TCGA-VD-A8KH 
       35.44        31.76        25.41        27.52        31.07        38.07 
TCGA-VD-A8KK TCGA-VD-A8KL TCGA-VD-AA8P TCGA-VD-AA8Q TCGA-WC-A87Y TCGA-WC-A882 
        2.10        20.98         2.83        20.91        43.20        36.56 
TCGA-WC-A883 TCGA-WC-A884 TCGA-YZ-A980 TCGA-YZ-A982 TCGA-YZ-A984 TCGA-YZ-A985 
        7.92         0.39        61.22        16.27        45.90        38.93 

subtype1 subtype2 subtype3 
    0.13     0.20     0.39 
subtype1 subtype2 subtype3 
   49.68    85.48    61.22 
subtype1 subtype2 subtype3 
  15.450   33.800   29.295 
[1] "0.1 - 49.7 (15.4)" "0.2 - 85.5 (33.8)" "0.4 - 61.2 (29.3)"
D4V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         3         9          9          3          1        4
  subtype2         9        13          8          3          0        0
  subtype3         0         5          8          4          0        0
D4V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE IIA         3        9        0
  STAGE IIB         9       13        5
  STAGE IIIA        9        8        8
  STAGE IIIB        3        3        4
  STAGE IIIC        1        0        0
  STAGE IV          4        0        0
[1] 6 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       T2 T3 T4
  subtype1  4  9 16
  subtype2  9 15  9
  subtype3  1  8  9
D4V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T2        4        9        1
  T3        9       15        8
  T4       16        9        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"
D4V5, binary
          cls
clus        0  1
  subtype1 18  4
  subtype2 22  0
  subtype3 11  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   18    4
  subtype2   22    0
  subtype3   11    0
   clus
vv  subtype1 subtype2 subtype3
  0       18       22       11
  1        4        0        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"
D4V6, binary
          cls
clus        0  1
  subtype1 12 17
  subtype2 14 19
  subtype3  9  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   12   17
  subtype2   14   19
  subtype3    9    9
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       12       14        9
  MALE         17       19        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"
D4V7, binary
          cls
clus        0  1
  subtype1 27  1
  subtype2 32  1
  subtype3 17  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   27    1
  subtype2   32    1
  subtype3   17    1
     clus
vv    subtype1 subtype2 subtype3
  NO        27       32       17
  YES        1        1        1
[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(5) Variable = MIRSEQ_CNMF
D5V1, survival
          sevent
clus2       0  1
  subtype1  5  3
  subtype2  5  3
  subtype3 11  0
  subtype4 24  1
  subtype5  9 14
  subtype6  3  2
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
       8        8       11       25       23        5 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
       3        3        0        1       14        2 
$subtype1
TCGA-RZ-AB0B TCGA-V4-A9ED TCGA-V4-A9F0 TCGA-VD-A8KL TCGA-VD-AA8N TCGA-WC-A882 
        4.90        35.44        31.07        20.98         1.45        36.56 
TCGA-YZ-A984 TCGA-YZ-A985 
       45.90        38.93 

$subtype2
TCGA-V3-A9ZX TCGA-V4-A9F3 TCGA-VD-A8KH TCGA-VD-A8KJ TCGA-WC-A87Y TCGA-WC-A883 
       15.45        28.70        38.07        37.81        43.20         7.92 
TCGA-YZ-A980 TCGA-YZ-A982 
       61.22        16.27 

$subtype3
TCGA-V3-A9ZY TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EH TCGA-V4-A9EM TCGA-V4-A9EW 
       15.09        40.96        44.32        22.03        31.76        39.81 
TCGA-V4-A9EY TCGA-VD-A8K7 TCGA-VD-AA8P TCGA-VD-AA8R TCGA-WC-A87T 
       27.52        47.97         2.83         0.20        85.48 

$subtype4
TCGA-WC-A87U TCGA-WC-A881 TCGA-V4-A9E5 TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9EO 
       51.98        35.01        82.16        24.53        33.80        25.41 
TCGA-V4-A9ET TCGA-V4-A9EZ TCGA-V4-A9F2 TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K9 
       44.78        19.69        24.13        20.84        41.29        46.82 
TCGA-VD-A8KA TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KO TCGA-VD-AA8M 
       38.73        44.52        26.99         0.62        26.14         0.20 
TCGA-VD-AA8S TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A884 TCGA-WC-A885 TCGA-WC-AA9E 
       14.04        55.99        41.36         0.39        22.55        27.55 
TCGA-YZ-A983 
       26.24 

$subtype5
TCGA-V4-A9EL TCGA-WC-AA9A TCGA-V4-A9E7 TCGA-V4-A9E8 TCGA-V4-A9EE TCGA-V4-A9EF 
       32.28        14.89        13.64        26.56        13.08        38.30 
TCGA-V4-A9EI TCGA-V4-A9EQ TCGA-V4-A9EU TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F1 
       12.79        14.96        23.31        41.72        24.00        30.84 
TCGA-V4-A9F5 TCGA-V4-A9F8 TCGA-VD-A8K8 TCGA-VD-A8KD TCGA-VD-A8KI TCGA-VD-A8KK 
        6.67        19.63        45.27         3.75        36.59         2.10 
TCGA-VD-A8KM TCGA-VD-A8KN TCGA-VD-AA8O TCGA-WC-A888 TCGA-WC-A88A 
        0.13         2.24        19.92        18.90         2.70 

$subtype6
TCGA-V4-A9EC TCGA-V4-A9ES TCGA-VD-A8KF TCGA-VD-AA8Q TCGA-VD-AA8T 
       24.43        49.68         1.32        20.91         1.61 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
    1.45     7.92     0.20     0.20     0.13     1.32 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
   45.90    61.22    85.48    82.16    45.27    49.68 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
  33.255   33.255   31.760   26.990   18.900   20.910 
[1] "1.4 - 45.9 (33.3)" "7.9 - 61.2 (33.3)" "0.2 - 85.5 (31.8)"
[4] "0.2 - 82.2 (27.0)" "0.1 - 45.3 (18.9)" "1.3 - 49.7 (20.9)"
D5V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         0         4          2          1          0        1
  subtype2         0         2          3          2          0        0
  subtype3         0         4          6          1          0        0
  subtype4         9         8          5          3          0        0
  subtype5         2         7          8          2          1        3
  subtype6         1         2          1          1          0        0
D5V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  STAGE IIA         0        0        0        9        2        1
  STAGE IIB         4        2        4        8        7        2
  STAGE IIIA        2        3        6        5        8        1
  STAGE IIIB        1        2        1        3        2        1
  STAGE IIIC        0        0        0        0        1        0
  STAGE IV          1        0        0        0        3        0
[1] 6 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T2 T3 T4
  subtype1  1  4  3
  subtype2  1  4  3
  subtype3  0  4  7
  subtype4  9 10  6
  subtype5  2  7 14
  subtype6  1  3  1
D5V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  T2        1        1        0        9        2        1
  T3        4        4        4       10        7        3
  T4        3        3        7        6       14        1
[1] 3 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V5, binary
          cls
clus        0  1
  subtype1  4  1
  subtype2  3  0
  subtype3  9  0
  subtype4 17  0
  subtype5 14  3
  subtype6  4  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    4    1
  subtype2    3    0
  subtype3    9    0
  subtype4   17    0
  subtype5   14    3
  subtype6    4    0
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  0        4        3        9       17       14        4
  1        1        0        0        0        3        0
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V6, binary
          cls
clus        0  1
  subtype1  5  3
  subtype2  3  5
  subtype3  4  7
  subtype4 12 13
  subtype5  8 15
  subtype6  3  2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5    3
  subtype2    3    5
  subtype3    4    7
  subtype4   12   13
  subtype5    8   15
  subtype6    3    2
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  FEMALE        5        3        4       12        8        3
  MALE          3        5        7       13       15        2
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V7, binary
          cls
clus        0  1
  subtype1  7  0
  subtype2  7  1
  subtype3 11  0
  subtype4 24  1
  subtype5 22  1
  subtype6  5  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7    0
  subtype2    7    1
  subtype3   11    0
  subtype4   24    1
  subtype5   22    1
  subtype6    5    0
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  NO         7        7       11       24       22        5
  YES        0        1        0        1        1        0
[1] 2 6
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(6) Variable = MIRSEQ_CHIERARCHICAL
D6V1, survival
          sevent
clus2       0  1
  subtype1 10  7
  subtype2 12  1
  subtype3 26  2
  subtype4  9 13
subtype1 subtype2 subtype3 subtype4 
      17       13       28       22 
subtype1 subtype2 subtype3 subtype4 
       7        1        2       13 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9ED TCGA-V4-A9EU TCGA-V4-A9F0 TCGA-V4-A9F1 
        4.90        15.45        35.44        23.31        31.07        30.84 
TCGA-V4-A9F3 TCGA-VD-A8KL TCGA-VD-A8KN TCGA-VD-AA8N TCGA-VD-AA8O TCGA-WC-A87Y 
       28.70        20.98         2.24         1.45        19.92        43.20 
TCGA-WC-A882 TCGA-WC-A883 TCGA-YZ-A980 TCGA-YZ-A984 TCGA-YZ-A985 
       36.56         7.92        61.22        45.90        38.93 

$subtype2
TCGA-V3-A9ZY TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EH TCGA-V4-A9EM 
       15.09        40.96        44.32        24.43        22.03        31.76 
TCGA-V4-A9EW TCGA-VD-A8K7 TCGA-VD-A8KH TCGA-VD-A8KJ TCGA-VD-AA8Q TCGA-VD-AA8R 
       39.81        47.97        38.07        37.81        20.91         0.20 
TCGA-WC-A87T 
       85.48 

$subtype3
TCGA-WC-A87U TCGA-WC-A881 TCGA-V4-A9E5 TCGA-V4-A9E8 TCGA-V4-A9EJ TCGA-V4-A9EK 
       51.98        35.01        82.16        26.56        24.53        33.80 
TCGA-V4-A9EO TCGA-V4-A9ET TCGA-V4-A9EY TCGA-V4-A9EZ TCGA-V4-A9F2 TCGA-V4-A9F4 
       25.41        44.78        27.52        19.69        24.13        20.84 
TCGA-V4-A9F7 TCGA-VD-A8K9 TCGA-VD-A8KA TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG 
       41.29        46.82        38.73        44.52        26.99         0.62 
TCGA-VD-A8KO TCGA-VD-AA8M TCGA-VD-AA8S TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A884 
       26.14         0.20        14.04        55.99        41.36         0.39 
TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A982 TCGA-YZ-A983 
       22.55        27.55        16.27        26.24 

$subtype4
TCGA-V4-A9EL TCGA-WC-AA9A TCGA-V4-A9E7 TCGA-V4-A9EE TCGA-V4-A9EF TCGA-V4-A9EI 
       32.28        14.89        13.64        13.08        38.30        12.79 
TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F5 TCGA-V4-A9F8 
       14.96        49.68        41.72        24.00         6.67        19.63 
TCGA-VD-A8K8 TCGA-VD-A8KD TCGA-VD-A8KF TCGA-VD-A8KI TCGA-VD-A8KK TCGA-VD-A8KM 
       45.27         3.75         1.32        36.59         2.10         0.13 
TCGA-VD-AA8P TCGA-VD-AA8T TCGA-WC-A888 TCGA-WC-A88A 
        2.83         1.61        18.90         2.70 

subtype1 subtype2 subtype3 subtype4 
    1.45     0.20     0.20     0.13 
subtype1 subtype2 subtype3 subtype4 
   61.22    85.48    82.16    49.68 
subtype1 subtype2 subtype3 subtype4 
  28.700   37.810   26.775   14.265 
[1] "1.4 - 61.2 (28.7)" "0.2 - 85.5 (37.8)" "0.2 - 82.2 (26.8)"
[4] "0.1 - 49.7 (14.3)"
D6V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1         7          5          1          1        1
  subtype2         0         6          5          2          0        0
  subtype3         9         8          7          4          0        0
  subtype4         2         6          8          3          0        3
D6V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE IIA         1        0        9        2
  STAGE IIB         7        6        8        6
  STAGE IIIA        5        5        7        8
  STAGE IIIB        1        2        4        3
  STAGE IIIC        1        0        0        0
  STAGE IV          1        0        0        3
[1] 6 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       T2 T3 T4
  subtype1  3  9  5
  subtype2  0  6  7
  subtype3  9 10  9
  subtype4  2  7 13
D6V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  T2        3        0        9        2
  T3        9        6       10        7
  T4        5        7        9       13
[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"
D6V5, binary
          cls
clus        0  1
  subtype1 10  1
  subtype2  9  0
  subtype3 19  0
  subtype4 13  3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10    1
  subtype2    9    0
  subtype3   19    0
  subtype4   13    3
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       10        9       19       13
  1        1        0        0        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"
D6V6, binary
          cls
clus        0  1
  subtype1 10  7
  subtype2  3 10
  subtype3 14 14
  subtype4  8 14
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10    7
  subtype2    3   10
  subtype3   14   14
  subtype4    8   14
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       10        3       14        8
  MALE          7       10       14       14
[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"
D6V7, binary
          cls
clus        0  1
  subtype1 15  1
  subtype2 13  0
  subtype3 27  1
  subtype4 21  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   15    1
  subtype2   13    0
  subtype3   27    1
  subtype4   21    1
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        15       13       27       21
  YES        1        0        1        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"

Clustering(7) Variable = MIRSEQ_MATURE_CNMF
D7V1, survival
          sevent
clus2       0  1
  subtype1  6 14
  subtype2  5  2
  subtype3 16  1
  subtype4  8  1
  subtype5  7  1
  subtype6  6  1
  subtype7  3  3
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
      20        7       17        9        8        7        6 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
      14        2        1        1        1        1        3 
$subtype1
TCGA-V4-A9EL TCGA-RZ-AB0B TCGA-V4-A9E7 TCGA-V4-A9E8 TCGA-V4-A9EE TCGA-V4-A9EI 
       32.28         4.90        13.64        26.56        13.08        12.79 
TCGA-V4-A9EQ TCGA-V4-A9EU TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F1 TCGA-V4-A9F3 
       14.96        23.31        41.72        24.00        30.84        28.70 
TCGA-V4-A9F5 TCGA-VD-A8KI TCGA-VD-A8KM TCGA-VD-A8KN TCGA-VD-AA8O TCGA-WC-A883 
        6.67        36.59         0.13         2.24        19.92         7.92 
TCGA-WC-A888 TCGA-WC-A88A 
       18.90         2.70 

$subtype2
TCGA-V3-A9ZX TCGA-VD-AA8N TCGA-WC-A87Y TCGA-WC-A882 TCGA-WC-A884 TCGA-YZ-A980 
       15.45         1.45        43.20        36.56         0.39        61.22 
TCGA-YZ-A984 
       45.90 

$subtype3
TCGA-WC-A87U TCGA-WC-A881 TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9EJ TCGA-V4-A9EK 
       51.98        35.01        15.09        82.16        24.53        33.80 
TCGA-V4-A9EM TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 
       31.76        44.78        39.81        20.84        41.29        47.97 
TCGA-VD-A8KA TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A880 TCGA-WC-A885 
       38.73        14.04        85.48        41.36        22.55 

$subtype4
TCGA-V4-A9E9 TCGA-V4-A9ED TCGA-V4-A9EH TCGA-V4-A9EY TCGA-V4-A9F0 TCGA-VD-A8KH 
       40.96        35.44        22.03        27.52        31.07        38.07 
TCGA-VD-A8KJ TCGA-VD-A8KK TCGA-YZ-A985 
       37.81         2.10        38.93 

$subtype5
TCGA-WC-AA9A TCGA-V4-A9EC TCGA-V4-A9EO TCGA-V4-A9ES TCGA-V4-A9F2 TCGA-VD-AA8P 
       14.89        24.43        25.41        49.68        24.13         2.83 
TCGA-VD-AA8T TCGA-WC-A87W 
        1.61        55.99 

$subtype6
TCGA-V4-A9EZ TCGA-V4-A9F8 TCGA-VD-A8KL TCGA-VD-AA8M TCGA-VD-AA8Q TCGA-WC-AA9E 
       19.69        19.63        20.98         0.20        20.91        27.55 
TCGA-YZ-A982 
       16.27 

$subtype7
TCGA-VD-A8K8 TCGA-VD-A8K9 TCGA-VD-A8KB TCGA-VD-A8KD TCGA-VD-A8KE TCGA-VD-A8KF 
       45.27        46.82        44.52         3.75        26.99         1.32 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
    0.13     0.39    14.04     2.10     1.61     0.20     1.32 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
   41.72    61.22    85.48    40.96    55.99    27.55    46.82 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
  16.930   36.560   38.730   35.440   24.280   19.690   35.755 
[1] "0.1 - 41.7 (16.9)"  "0.4 - 61.2 (36.6)"  "14.0 - 85.5 (38.7)"
[4] "2.1 - 41.0 (35.4)"  "1.6 - 56.0 (24.3)"  "0.2 - 27.6 (19.7)" 
[7] "1.3 - 46.8 (35.8)" 
D7V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1         6          8          1          1        3
  subtype2         0         4          1          1          0        0
  subtype3         2         7          6          2          0        0
  subtype4         0         1          5          3          0        0
  subtype5         3         2          3          0          0        0
  subtype6         2         3          1          1          0        0
  subtype7         2         2          0          1          0        1
D7V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  STAGE IIA         1        0        2        0        3        2        2
  STAGE IIB         6        4        7        1        2        3        2
  STAGE IIIA        8        1        6        5        3        1        0
  STAGE IIIB        1        1        2        3        0        1        1
  STAGE IIIC        1        0        0        0        0        0        0
  STAGE IV          3        0        0        0        0        0        1
[1] 6 7
[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       T2 T3 T4
  subtype1  1  7 12
  subtype2  2  4  1
  subtype3  2  8  7
  subtype4  0  2  7
  subtype5  3  4  1
  subtype6  2  3  2
  subtype7  2  2  2
D7V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  T2        1        2        2        0        3        2        2
  T3        7        4        8        2        4        3        2
  T4       12        1        7        7        1        2        2
[1] 3 7
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V5, binary
          cls
clus        0  1
  subtype1 14  3
  subtype2  4  0
  subtype3 14  0
  subtype4  5  0
  subtype5  7  0
  subtype6  4  0
  subtype7  0  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   14    3
  subtype2    4    0
  subtype3   14    0
  subtype4    5    0
  subtype5    7    0
  subtype6    4    0
  subtype7    0    1
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  0       14        4       14        5        7        4        0
  1        3        0        0        0        0        0        1
[1] 2 7
[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  9 11
  subtype2  3  4
  subtype3  4 13
  subtype4  2  7
  subtype5  7  1
  subtype6  3  4
  subtype7  4  2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   11
  subtype2    3    4
  subtype3    4   13
  subtype4    2    7
  subtype5    7    1
  subtype6    3    4
  subtype7    4    2
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  FEMALE        9        3        4        2        7        3        4
  MALE         11        4       13        7        1        4        2
[1] 2 7
[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 18  1
  subtype2  6  1
  subtype3 17  0
  subtype4  9  0
  subtype5  8  0
  subtype6  6  1
  subtype7  6  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   18    1
  subtype2    6    1
  subtype3   17    0
  subtype4    9    0
  subtype5    8    0
  subtype6    6    1
  subtype7    6    0
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  NO        18        6       17        9        8        6        6
  YES        1        1        0        0        0        1        0
[1] 2 7
[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_MATURE_CHIERARCHICAL
D8V1, survival
          sevent
clus2       0  1
  subtype1  9  9
  subtype2 26  2
  subtype3  6 10
  subtype4 10  2
subtype1 subtype2 subtype3 subtype4 
      18       28       16       12 
subtype1 subtype2 subtype3 subtype4 
       9        2       10        2 
$subtype1
TCGA-V4-A9EL TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9ED TCGA-V4-A9EI TCGA-V4-A9EU 
       32.28         4.90        15.45        35.44        12.79        23.31 
TCGA-V4-A9EX TCGA-V4-A9F0 TCGA-V4-A9F3 TCGA-VD-A8KH TCGA-VD-A8KI TCGA-VD-A8KK 
       24.00        31.07        28.70        38.07        36.59         2.10 
TCGA-VD-A8KN TCGA-VD-AA8N TCGA-WC-A87Y TCGA-WC-A883 TCGA-WC-A88A TCGA-YZ-A980 
        2.24         1.45        43.20         7.92         2.70        61.22 

$subtype2
TCGA-WC-A87U TCGA-WC-A881 TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9EC TCGA-V4-A9EH 
       51.98        35.01        15.09        82.16        24.43        22.03 
TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9EO TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9EZ 
       24.53        33.80        25.41        44.78        39.81        19.69 
TCGA-V4-A9F2 TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 TCGA-VD-A8KA 
       24.13        20.84        41.29        47.97        46.82        38.73 
TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-AA8M TCGA-VD-AA8Q TCGA-VD-AA8S TCGA-WC-A87T 
       44.52        26.99         0.20        20.91        14.04        85.48 
TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A885 TCGA-WC-AA9E 
       55.99        41.36        22.55        27.55 

$subtype3
TCGA-WC-AA9A TCGA-V4-A9E7 TCGA-V4-A9EE TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EV 
       14.89        13.64        13.08        14.96        49.68        41.72 
TCGA-V4-A9F1 TCGA-V4-A9F5 TCGA-VD-A8K8 TCGA-VD-A8KD TCGA-VD-A8KF TCGA-VD-A8KM 
       30.84         6.67        45.27         3.75         1.32         0.13 
TCGA-VD-AA8O TCGA-VD-AA8P TCGA-VD-AA8T TCGA-WC-A888 
       19.92         2.83         1.61        18.90 

$subtype4
TCGA-V4-A9E8 TCGA-V4-A9E9 TCGA-V4-A9EM TCGA-V4-A9EY TCGA-V4-A9F8 TCGA-VD-A8KJ 
       26.56        40.96        31.76        27.52        19.63        37.81 
TCGA-VD-A8KL TCGA-WC-A882 TCGA-WC-A884 TCGA-YZ-A982 TCGA-YZ-A984 TCGA-YZ-A985 
       20.98        36.56         0.39        16.27        45.90        38.93 

subtype1 subtype2 subtype3 subtype4 
    1.45     0.20     0.13     0.39 
subtype1 subtype2 subtype3 subtype4 
   61.22    85.48    49.68    45.90 
subtype1 subtype2 subtype3 subtype4 
  23.655   30.675   14.265   29.640 
[1] "1.4 - 61.2 (23.7)" "0.2 - 85.5 (30.7)" "0.1 - 49.7 (14.3)"
[4] "0.4 - 45.9 (29.6)"
D8V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1         3          7          3          1        2
  subtype2         7        11          7          3          0        0
  subtype3         2         7          4          1          0        2
  subtype4         0         4          6          2          0        0
D8V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE IIA         1        7        2        0
  STAGE IIB         3       11        7        4
  STAGE IIIA        7        7        4        6
  STAGE IIIB        3        3        1        2
  STAGE IIIC        1        0        0        0
  STAGE IV          2        0        2        0
[1] 6 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       T2 T3 T4
  subtype1  2  6 10
  subtype2  7 13  8
  subtype3  2  8  6
  subtype4  1  3  8
D8V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  T2        2        7        2        1
  T3        6       13        8        3
  T4       10        8        6        8
[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"
D8V5, binary
          cls
clus        0  1
  subtype1 10  2
  subtype2 21  0
  subtype3 10  2
  subtype4  7  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10    2
  subtype2   21    0
  subtype3   10    2
  subtype4    7    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       10       21       10        7
  1        2        0        2        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"
D8V6, binary
          cls
clus        0  1
  subtype1  6 12
  subtype2 11 17
  subtype3  8  8
  subtype4  7  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    6   12
  subtype2   11   17
  subtype3    8    8
  subtype4    7    5
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        6       11        8        7
  MALE         12       17        8        5
[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 15  2
  subtype2 27  1
  subtype3 16  0
  subtype4 12  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   15    2
  subtype2   27    1
  subtype3   16    0
  subtype4   12    0
     clus
vv    subtype1 subtype2 subtype3 subtype4
  NO        15       27       16       12
  YES        2        1        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"
