[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/15096076/UVM-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/UVM-TP/15952300/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 
22 36 22 
 1  2  3 
22 36 22 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3 
33 18 29 
 1  2  3 
33 18 29 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2  3 
30 15 35 
 1  2  3 
30 15 35 
[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 
34 17 29 
 1  2  3 
34 17 29 
[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 
32 28 14 
 1  2  3 
32 28 14 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
 1  2  3  4  5  6 
 5 12 16 16 15 10 
 1  2  3  4  5  6 
 5 12 16 16 15 10 
[1] "data2feature, selection=ALL"
 [1] "YEARS_TO_BIRTH"                        
 [2] "VITAL_STATUS"                          
 [3] "DAYS_TO_DEATH"                         
 [4] "DAYS_TO_LAST_FOLLOWUP"                 
 [5] "NEOPLASM_DISEASESTAGE"                 
 [6] "PATHOLOGY_T_STAGE"                     
 [7] "PATHOLOGY_N_STAGE"                     
 [8] "PATHOLOGY_M_STAGE"                     
 [9] "DCC_UPLOAD_DATE"                       
[10] "GENDER"                                
[11] "RADIATIONS_RADIATION_REGIMENINDICATION"
[12] "RACE"                                  
[13] "ETHNICITY"                             
[14] "BATCH_NUMBER"                          

Input Data has 14 rows and 80 columns.

[1] "Batch" "14"   
[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=13,	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=64,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
[1] "exclude grep('FOLLOWUP', vnms) to deal with survival parameters seperately"
Variable 5:'NEOPLASM_DISEASESTAGE':	nDistinctValues=6,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 6:'PATHOLOGY_T_STAGE':	nDistinctValues=11,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 7:'PATHOLOGY_N_STAGE':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 8:'PATHOLOGY_M_STAGE':	nDistinctValues=4,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 9:'DCC_UPLOAD_DATE':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "DCC_UPLOAD_DATE excluded in the analysis because there is no case of (both >= 3) in the table below"
              19-2-2015 2-4-2015
freq.values   "1"       "79"    
freq.contrast "79"      "1"     
both >= 3     "FALSE"   "FALSE" 
Variable 10:'GENDER':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 11:'RADIATIONS_RADIATION_REGIMENINDICATION':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "RADIATIONS_RADIATION_REGIMENINDICATION is excluded in the analysis because there is no more than two cases of (unique non-NA values)"
Variable 12:'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 13:'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"               
Variable 14:'BATCH_NUMBER':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "BATCH_NUMBER excluded in the analysis because there is no case of (both >= 3) in the table below"
              B417.12.0 B417.15.0
freq.values   "1"       "79"     
freq.contrast "79"      "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 5 non-survival variables.
[1] "* survival variables: "
[1] "DAYS_TO_DEATH_OR_LAST_FUP" "VITAL_STATUS"             
[1] "* non-survival variables: "
[1] "YEARS_TO_BIRTH"        "NEOPLASM_DISEASESTAGE" "PATHOLOGY_T_STAGE"    
[4] "PATHOLOGY_M_STAGE"     "GENDER"               
YEARS_TO_BIRTH, nv=40, binary=FALSE, numeric=TRUE
NEOPLASM_DISEASESTAGE, 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

Clustering(1) Variable = CN_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 17  5
  subtype2 35  1
  subtype3 15  7
subtype1 subtype2 subtype3 
      22       36       22 
subtype1 subtype2 subtype3 
       5        1        7 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9E7 TCGA-V4-A9EF TCGA-V4-A9EI TCGA-V4-A9EL 
        4.90         4.50        13.64        27.09        13.22        23.44 
TCGA-V4-A9EU TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F0 TCGA-V4-A9F1 TCGA-V4-A9F3 
       23.31        27.48        24.00        24.10        21.73        22.03 
TCGA-V4-A9F5 TCGA-VD-A8K8 TCGA-VD-A8KI TCGA-VD-A8KL TCGA-VD-A8KM TCGA-VD-A8KN 
        6.67        16.87         1.25        20.98         0.13         2.24 
TCGA-VD-AA8N TCGA-WC-A87Y TCGA-WC-A888 TCGA-WC-A88A 
        1.45        31.40        10.13         2.70 

$subtype2
TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EH 
        4.04        74.53        30.38        24.69        24.43        22.03 
TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9EM TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9EY 
       12.56        18.64        22.03        31.66        30.05        25.02 
TCGA-V4-A9EZ TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 TCGA-VD-A8KA 
       19.69        20.22        32.28         0.10         0.46        37.28 
TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KJ TCGA-VD-A8KO TCGA-VD-AA8M 
       35.31        26.99         0.66        31.59        26.14         0.20 
TCGA-VD-AA8Q TCGA-VD-AA8R TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A87U TCGA-WC-A87W 
        0.23         0.20        14.04        70.65        51.98        45.57 
TCGA-WC-A880 TCGA-WC-A881 TCGA-WC-A884 TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A983 
       31.99        22.82         0.39        10.36        14.20        17.98 

$subtype3
TCGA-V4-A9E8 TCGA-V4-A9ED TCGA-V4-A9EE TCGA-V4-A9EO TCGA-V4-A9EQ TCGA-V4-A9ES 
       26.56        28.41        13.08        19.53        14.96        37.81 
TCGA-V4-A9F2 TCGA-V4-A9F8 TCGA-VD-A8KD TCGA-VD-A8KF TCGA-VD-A8KH TCGA-VD-A8KK 
       12.20        19.63         3.75         1.32         0.33         2.10 
TCGA-VD-AA8O TCGA-VD-AA8P TCGA-VD-AA8T TCGA-WC-A882 TCGA-WC-A883 TCGA-WC-AA9A 
        7.50         2.83         0.49        11.31         7.92        14.89 
TCGA-YZ-A980 TCGA-YZ-A982 TCGA-YZ-A984 TCGA-YZ-A985 
       52.64        16.27        42.08        25.81 

subtype1 subtype2 subtype3 
    0.13     0.10     0.33 
subtype1 subtype2 subtype3 
   31.40    74.53    52.64 
subtype1 subtype2 subtype3 
  15.255   22.425   13.985 
[1] "0.1 - 31.4 (15.3)" "0.1 - 74.5 (22.4)" "0.3 - 52.6 (14.0)"
D1V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1         8          5          3          1        3
  subtype2         9        14          9          4          0        0
  subtype3         2         5         11          3          0        1
D1V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE IIA         1        9        2
  STAGE IIB         8       14        5
  STAGE IIIA        5        9       11
  STAGE IIIB        3        4        3
  STAGE IIIC        1        0        0
  STAGE IV          3        0        1
[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  2  8 12
  subtype2  9 15 12
  subtype3  3  9 10
D1V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T2        2        9        3
  T3        8       15        9
  T4       12       12       10
[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"
D1V5, binary
          cls
clus        0  1
  subtype1 13  3
  subtype2 25  0
  subtype3 13  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   13    3
  subtype2   25    0
  subtype3   13    1
   clus
vv  subtype1 subtype2 subtype3
  0       13       25       13
  1        3        0        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"
D1V6, binary
          cls
clus        0  1
  subtype1 10 12
  subtype2 15 21
  subtype3 10 12
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10   12
  subtype2   15   21
  subtype3   10   12
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       10       15       10
  MALE         12       21       12
[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 23 10
  subtype2 16  2
  subtype3 28  1
subtype1 subtype2 subtype3 
      33       18       29 
subtype1 subtype2 subtype3 
      10        2        1 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9E7 TCGA-V4-A9E8 TCGA-V4-A9EE TCGA-V4-A9EF 
        4.90         4.50        13.64        26.56        13.08        27.09 
TCGA-V4-A9EI TCGA-V4-A9EL TCGA-V4-A9EQ TCGA-V4-A9EU TCGA-V4-A9EV TCGA-V4-A9EX 
       13.22        23.44        14.96        23.31        27.48        24.00 
TCGA-V4-A9F0 TCGA-V4-A9F1 TCGA-V4-A9F3 TCGA-V4-A9F5 TCGA-V4-A9F8 TCGA-VD-A8K8 
       24.10        21.73        22.03         6.67        19.63        16.87 
TCGA-VD-A8KD TCGA-VD-A8KI TCGA-VD-A8KK TCGA-VD-A8KL TCGA-VD-A8KM TCGA-VD-A8KN 
        3.75         1.25         2.10        20.98         0.13         2.24 
TCGA-VD-AA8N TCGA-VD-AA8O TCGA-VD-AA8T TCGA-WC-A87Y TCGA-WC-A883 TCGA-WC-A888 
        1.45         7.50         0.49        31.40         7.92        10.13 
TCGA-WC-A88A TCGA-YZ-A984 TCGA-YZ-A985 
        2.70        42.08        25.81 

$subtype2
TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9ED TCGA-V4-A9EH TCGA-V4-A9EM TCGA-V4-A9EO 
        4.04        74.53        28.41        22.03        22.03        19.53 
TCGA-V4-A9ES TCGA-V4-A9EW TCGA-V4-A9EZ TCGA-V4-A9F2 TCGA-VD-A8KF TCGA-VD-A8KH 
       37.81        30.05        19.69        12.20         1.32         0.33 
TCGA-VD-AA8P TCGA-VD-AA8R TCGA-WC-A87W TCGA-WC-A882 TCGA-WC-AA9A TCGA-YZ-A980 
        2.83         0.20        45.57        11.31        14.89        52.64 

$subtype3
TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9ET 
       30.38        24.69        24.43        12.56        18.64        31.66 
TCGA-V4-A9EY TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 TCGA-VD-A8KA 
       25.02        20.22        32.28         0.10         0.46        37.28 
TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KJ TCGA-VD-A8KO TCGA-VD-AA8M 
       35.31        26.99         0.66        31.59        26.14         0.20 
TCGA-VD-AA8Q TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A87U TCGA-WC-A880 TCGA-WC-A881 
        0.23        14.04        70.65        51.98        31.99        22.82 
TCGA-WC-A884 TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A982 TCGA-YZ-A983 
        0.39        10.36        14.20        16.27        17.98 

subtype1 subtype2 subtype3 
    0.13     0.20     0.10 
subtype1 subtype2 subtype3 
   42.08    74.53    70.65 
subtype1 subtype2 subtype3 
   13.64    19.61    22.82 
[1] "0.1 - 42.1 (13.6)" "0.2 - 74.5 (19.6)" "0.1 - 70.7 (22.8)"
D2V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         2        11         11          3          1        4
  subtype2         2         5          7          4          0        0
  subtype3         8        11          7          3          0        0
D2V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE IIA         2        2        8
  STAGE IIB        11        5       11
  STAGE IIIA       11        7        7
  STAGE IIIB        3        4        3
  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  3 12 18
  subtype2  3  8  7
  subtype3  8 12  9
D2V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T2        3        3        8
  T3       12        8       12
  T4       18        7        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"
D2V5, binary
          cls
clus        0  1
  subtype1 20  4
  subtype2 13  0
  subtype3 18  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   20    4
  subtype2   13    0
  subtype3   18    0
   clus
vv  subtype1 subtype2 subtype3
  0       20       13       18
  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"
D2V6, binary
          cls
clus        0  1
  subtype1 14 19
  subtype2 10  8
  subtype3 11 18
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   14   19
  subtype2   10    8
  subtype3   11   18
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       14       10       11
  MALE         19        8       18
[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 = MRNASEQ_CNMF
D3V1, survival
          sevent
clus2       0  1
  subtype1 19 11
  subtype2 14  1
  subtype3 34  1
subtype1 subtype2 subtype3 
      30       15       35 
subtype1 subtype2 subtype3 
      11        1        1 
$subtype1
TCGA-RZ-AB0B TCGA-V4-A9E7 TCGA-V4-A9E8 TCGA-V4-A9EE TCGA-V4-A9EF TCGA-V4-A9EI 
        4.90        13.64        26.56        13.08        27.09        13.22 
TCGA-V4-A9EL TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EU TCGA-V4-A9EV TCGA-V4-A9EX 
       23.44        14.96        37.81        23.31        27.48        24.00 
TCGA-V4-A9F1 TCGA-V4-A9F3 TCGA-V4-A9F5 TCGA-V4-A9F8 TCGA-VD-A8K8 TCGA-VD-A8KD 
       21.73        22.03         6.67        19.63        16.87         3.75 
TCGA-VD-A8KF TCGA-VD-A8KI TCGA-VD-A8KK TCGA-VD-A8KM TCGA-VD-A8KN TCGA-VD-AA8N 
        1.32         1.25         2.10         0.13         2.24         1.45 
TCGA-VD-AA8O TCGA-VD-AA8T TCGA-WC-A888 TCGA-WC-A88A TCGA-WC-AA9A TCGA-YZ-A985 
        7.50         0.49        10.13         2.70        14.89        25.81 

$subtype2
TCGA-V3-A9ZX TCGA-V4-A9ED TCGA-V4-A9EM TCGA-V4-A9EY TCGA-V4-A9F0 TCGA-VD-A8KL 
        4.50        28.41        22.03        25.02        24.10        20.98 
TCGA-VD-AA8P TCGA-VD-AA8Q TCGA-WC-A87Y TCGA-WC-A882 TCGA-WC-A883 TCGA-WC-A884 
        2.83         0.23        31.40        11.31         7.92         0.39 
TCGA-YZ-A980 TCGA-YZ-A982 TCGA-YZ-A984 
       52.64        16.27        42.08 

$subtype3
TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EH 
        4.04        74.53        30.38        24.69        24.43        22.03 
TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9EO TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9EZ 
       12.56        18.64        19.53        31.66        30.05        19.69 
TCGA-V4-A9F2 TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 TCGA-VD-A8KA 
       12.20        20.22        32.28         0.10         0.46        37.28 
TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KH TCGA-VD-A8KJ TCGA-VD-A8KO 
       35.31        26.99         0.66         0.33        31.59        26.14 
TCGA-VD-AA8M TCGA-VD-AA8R TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A87U TCGA-WC-A87W 
        0.20         0.20        14.04        70.65        51.98        45.57 
TCGA-WC-A880 TCGA-WC-A881 TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A983 
       31.99        22.82        10.36        14.20        17.98 

subtype1 subtype2 subtype3 
    0.13     0.23     0.10 
subtype1 subtype2 subtype3 
   37.81    52.64    74.53 
subtype1 subtype2 subtype3 
   13.43    20.98    22.03 
[1] "0.1 - 37.8 (13.4)" "0.2 - 52.6 (21.0)" "0.1 - 74.5 (22.0)"
D3V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         3         8         11          3          1        4
  subtype2         0         6          5          3          0        0
  subtype3         9        13          9          4          0        0
D3V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE IIA         3        0        9
  STAGE IIB         8        6       13
  STAGE IIIA       11        5        9
  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  3  9 18
  subtype2  2  8  5
  subtype3  9 15 11
D3V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T2        3        2        9
  T3        9        8       15
  T4       18        5       11
[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"
D3V5, binary
          cls
clus        0  1
  subtype1 18  4
  subtype2 10  0
  subtype3 23  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   18    4
  subtype2   10    0
  subtype3   23    0
   clus
vv  subtype1 subtype2 subtype3
  0       18       10       23
  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"
D3V6, binary
          cls
clus        0  1
  subtype1 13 17
  subtype2  8  7
  subtype3 14 21
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   13   17
  subtype2    8    7
  subtype3   14   21
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       13        8       14
  MALE         17        7       21
[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(4) Variable = MRNASEQ_CHIERARCHICAL
D4V1, survival
          sevent
clus2       0  1
  subtype1 18 11
  subtype2 32  1
  subtype3 17  1
subtype1 subtype2 subtype3 
      29       33       18 
subtype1 subtype2 subtype3 
      11        1        1 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9E7 TCGA-V4-A9E8 TCGA-V4-A9EE TCGA-V4-A9EF 
        4.90         4.50        13.64        26.56        13.08        27.09 
TCGA-V4-A9EI TCGA-V4-A9EL TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EU TCGA-V4-A9EV 
       13.22        23.44        14.96        37.81        23.31        27.48 
TCGA-V4-A9EX TCGA-V4-A9F1 TCGA-V4-A9F3 TCGA-V4-A9F5 TCGA-V4-A9F8 TCGA-VD-A8K8 
       24.00        21.73        22.03         6.67        19.63        16.87 
TCGA-VD-A8KD TCGA-VD-A8KF TCGA-VD-A8KI TCGA-VD-A8KM TCGA-VD-A8KN TCGA-VD-AA8N 
        3.75         1.32         1.25         0.13         2.24         1.45 
TCGA-VD-AA8O TCGA-VD-AA8T TCGA-WC-A888 TCGA-WC-A88A TCGA-WC-AA9A 
        7.50         0.49        10.13         2.70        14.89 

$subtype2
TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EH 
        4.04        74.53        30.38        24.69        24.43        22.03 
TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9EZ TCGA-V4-A9F2 
       12.56        18.64        31.66        30.05        19.69        12.20 
TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8K9 TCGA-VD-A8KA TCGA-VD-A8KB 
       20.22        32.28         0.10         0.46        37.28        35.31 
TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KJ TCGA-VD-A8KO TCGA-VD-AA8M TCGA-VD-AA8R 
       26.99         0.66        31.59        26.14         0.20         0.20 
TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A87U TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A881 
       14.04        70.65        51.98        45.57        31.99        22.82 
TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A983 
       10.36        14.20        17.98 

$subtype3
TCGA-V4-A9ED TCGA-V4-A9EM TCGA-V4-A9EO TCGA-V4-A9EY TCGA-V4-A9F0 TCGA-VD-A8KH 
       28.41        22.03        19.53        25.02        24.10         0.33 
TCGA-VD-A8KK TCGA-VD-A8KL TCGA-VD-AA8P TCGA-VD-AA8Q TCGA-WC-A87Y TCGA-WC-A882 
        2.10        20.98         2.83         0.23        31.40        11.31 
TCGA-WC-A883 TCGA-WC-A884 TCGA-YZ-A980 TCGA-YZ-A982 TCGA-YZ-A984 TCGA-YZ-A985 
        7.92         0.39        52.64        16.27        42.08        25.81 

subtype1 subtype2 subtype3 
    0.13     0.10     0.23 
subtype1 subtype2 subtype3 
   37.81    74.53    52.64 
subtype1 subtype2 subtype3 
  13.220   22.820   20.255 
[1] "0.1 - 37.8 (13.2)" "0.1 - 74.5 (22.8)" "0.2 - 52.6 (20.3)"
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"

Clustering(5) Variable = MIRSEQ_CNMF
D5V1, survival
          sevent
clus2       0  1
  subtype1 27  7
  subtype2 12  5
  subtype3 28  1
subtype1 subtype2 subtype3 
      34       17       29 
subtype1 subtype2 subtype3 
       7        5        1 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9E8 TCGA-V4-A9ED TCGA-V4-A9EE TCGA-V4-A9EF 
        4.90         4.50        26.56        28.41        13.08        27.09 
TCGA-V4-A9EH TCGA-V4-A9EI TCGA-V4-A9EL TCGA-V4-A9EM TCGA-V4-A9EU TCGA-V4-A9EX 
       22.03        13.22        23.44        22.03        23.31        24.00 
TCGA-V4-A9F0 TCGA-V4-A9F1 TCGA-V4-A9F3 TCGA-V4-A9F8 TCGA-VD-A8KH TCGA-VD-A8KI 
       24.10        21.73        22.03        19.63         0.33         1.25 
TCGA-VD-A8KJ TCGA-VD-A8KK TCGA-VD-A8KL TCGA-VD-A8KM TCGA-VD-A8KN TCGA-VD-AA8N 
       31.59         2.10        20.98         0.13         2.24         1.45 
TCGA-VD-AA8O TCGA-VD-AA8P TCGA-VD-AA8Q TCGA-WC-A87Y TCGA-WC-A882 TCGA-WC-A883 
        7.50         2.83         0.23        31.40        11.31         7.92 
TCGA-WC-A888 TCGA-WC-A88A TCGA-YZ-A980 TCGA-YZ-A984 
       10.13         2.70        52.64        42.08 

$subtype2
TCGA-V3-A9ZY TCGA-V4-A9E7 TCGA-V4-A9EC TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EV 
        4.04        13.64        24.43        14.96        37.81        27.48 
TCGA-V4-A9EW TCGA-V4-A9F5 TCGA-VD-A8K7 TCGA-VD-A8K8 TCGA-VD-A8KD TCGA-VD-A8KF 
       30.05         6.67         0.10        16.87         3.75         1.32 
TCGA-VD-AA8R TCGA-VD-AA8T TCGA-WC-A87T TCGA-WC-AA9A TCGA-YZ-A985 
        0.20         0.49        70.65        14.89        25.81 

$subtype3
TCGA-V4-A9E5 TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9EO 
       74.53        30.38        24.69        12.56        18.64        19.53 
TCGA-V4-A9ET TCGA-V4-A9EY TCGA-V4-A9EZ TCGA-V4-A9F2 TCGA-V4-A9F4 TCGA-V4-A9F7 
       31.66        25.02        19.69        12.20        20.22        32.28 
TCGA-VD-A8K9 TCGA-VD-A8KA TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KO 
        0.46        37.28        35.31        26.99         0.66        26.14 
TCGA-VD-AA8M TCGA-VD-AA8S TCGA-WC-A87U TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A881 
        0.20        14.04        51.98        45.57        31.99        22.82 
TCGA-WC-A884 TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A982 TCGA-YZ-A983 
        0.39        10.36        14.20        16.27        17.98 

subtype1 subtype2 subtype3 
    0.13     0.10     0.20 
subtype1 subtype2 subtype3 
   52.64    70.65    74.53 
subtype1 subtype2 subtype3 
  16.425   14.890   20.220 
[1] "0.1 - 52.6 (16.4)" "0.1 - 70.7 (14.9)" "0.2 - 74.5 (20.2)"
D5V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1        14         10          5          1        2
  subtype2         2         5          7          1          0        2
  subtype3         9         8          8          4          0        0
D5V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE IIA         1        2        9
  STAGE IIB        14        5        8
  STAGE IIIA       10        7        8
  STAGE IIIB        5        1        4
  STAGE IIIC        1        0        0
  STAGE IV          2        2        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  3 16 15
  subtype2  2  6  9
  subtype3  9 10 10
D5V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T2        3        2        9
  T3       16        6       10
  T4       15        9       10
[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"
D5V5, binary
          cls
clus        0  1
  subtype1 22  2
  subtype2  9  2
  subtype3 20  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   22    2
  subtype2    9    2
  subtype3   20    0
   clus
vv  subtype1 subtype2 subtype3
  0       22        9       20
  1        2        2        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"
D5V6, binary
          cls
clus        0  1
  subtype1 11 23
  subtype2 10  7
  subtype3 14 15
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   23
  subtype2   10    7
  subtype3   14   15
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       11       10       14
  MALE         23        7       15
[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(6) Variable = MIRSEQ_CHIERARCHICAL
D6V1, survival
          sevent
clus2       0  1
  subtype1 15  2
  subtype2 13  0
  subtype3 26  2
  subtype4 13  9
subtype1 subtype2 subtype3 subtype4 
      17       13       28       22 
subtype1 subtype2 subtype3 subtype4 
       2        0        2        9 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9ED TCGA-V4-A9EU TCGA-V4-A9F0 TCGA-V4-A9F1 
        4.90         4.50        28.41        23.31        24.10        21.73 
TCGA-V4-A9F3 TCGA-VD-A8KL TCGA-VD-A8KN TCGA-VD-AA8N TCGA-VD-AA8O TCGA-WC-A87Y 
       22.03        20.98         2.24         1.45         7.50        31.40 
TCGA-WC-A882 TCGA-WC-A883 TCGA-YZ-A980 TCGA-YZ-A984 TCGA-YZ-A985 
       11.31         7.92        52.64        42.08        25.81 

$subtype2
TCGA-V3-A9ZY TCGA-V4-A9E9 TCGA-V4-A9EA TCGA-V4-A9EC TCGA-V4-A9EH TCGA-V4-A9EM 
        4.04        30.38        24.69        24.43        22.03        22.03 
TCGA-V4-A9EW TCGA-VD-A8K7 TCGA-VD-A8KH TCGA-VD-A8KJ TCGA-VD-AA8Q TCGA-VD-AA8R 
       30.05         0.10         0.33        31.59         0.23         0.20 
TCGA-WC-A87T 
       70.65 

$subtype3
TCGA-V4-A9E5 TCGA-V4-A9E8 TCGA-V4-A9EJ TCGA-V4-A9EK TCGA-V4-A9EO TCGA-V4-A9ET 
       74.53        26.56        12.56        18.64        19.53        31.66 
TCGA-V4-A9EY TCGA-V4-A9EZ TCGA-V4-A9F2 TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K9 
       25.02        19.69        12.20        20.22        32.28         0.46 
TCGA-VD-A8KA TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-A8KG TCGA-VD-A8KO TCGA-VD-AA8M 
       37.28        35.31        26.99         0.66        26.14         0.20 
TCGA-VD-AA8S TCGA-WC-A87U TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A881 TCGA-WC-A884 
       14.04        51.98        45.57        31.99        22.82         0.39 
TCGA-WC-A885 TCGA-WC-AA9E TCGA-YZ-A982 TCGA-YZ-A983 
       10.36        14.20        16.27        17.98 

$subtype4
TCGA-V4-A9E7 TCGA-V4-A9EE TCGA-V4-A9EF TCGA-V4-A9EI TCGA-V4-A9EL TCGA-V4-A9EQ 
       13.64        13.08        27.09        13.22        23.44        14.96 
TCGA-V4-A9ES TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F5 TCGA-V4-A9F8 TCGA-VD-A8K8 
       37.81        27.48        24.00         6.67        19.63        16.87 
TCGA-VD-A8KD TCGA-VD-A8KF TCGA-VD-A8KI TCGA-VD-A8KK TCGA-VD-A8KM TCGA-VD-AA8P 
        3.75         1.32         1.25         2.10         0.13         2.83 
TCGA-VD-AA8T TCGA-WC-A888 TCGA-WC-A88A TCGA-WC-AA9A 
        0.49        10.13         2.70        14.89 

subtype1 subtype2 subtype3 subtype4 
    1.45     0.10     0.20     0.13 
subtype1 subtype2 subtype3 subtype4 
   52.64    70.65    74.53    37.81 
subtype1 subtype2 subtype3 subtype4 
  21.730   22.030   19.955   13.150 
[1] "1.4 - 52.6 (21.7)" "0.1 - 70.7 (22.0)" "0.2 - 74.5 (20.0)"
[4] "0.1 - 37.8 (13.2)"
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"

Clustering(7) Variable = MIRSEQ_MATURE_CNMF
D7V1, survival
          sevent
clus2       0  1
  subtype1 24  8
  subtype2 27  1
  subtype3 10  4
subtype1 subtype2 subtype3 
      32       28       14 
subtype1 subtype2 subtype3 
       8        1        4 
$subtype1
TCGA-RZ-AB0B TCGA-V3-A9ZX TCGA-V4-A9E7 TCGA-V4-A9E8 TCGA-V4-A9ED TCGA-V4-A9EE 
        4.90         4.50        13.64        26.56        28.41        13.08 
TCGA-V4-A9EI TCGA-V4-A9EL TCGA-V4-A9EU TCGA-V4-A9EV TCGA-V4-A9EX TCGA-V4-A9F0 
       13.22        23.44        23.31        27.48        24.00        24.10 
TCGA-V4-A9F1 TCGA-V4-A9F3 TCGA-V4-A9F8 TCGA-VD-A8KH TCGA-VD-A8KI TCGA-VD-A8KJ 
       21.73        22.03        19.63         0.33         1.25        31.59 
TCGA-VD-A8KK TCGA-VD-A8KL TCGA-VD-A8KM TCGA-VD-A8KN TCGA-VD-AA8N TCGA-VD-AA8O 
        2.10        20.98         0.13         2.24         1.45         7.50 
TCGA-WC-A87Y TCGA-WC-A882 TCGA-WC-A883 TCGA-WC-A884 TCGA-WC-A888 TCGA-WC-A88A 
       31.40        11.31         7.92         0.39        10.13         2.70 
TCGA-YZ-A980 TCGA-YZ-A984 
       52.64        42.08 

$subtype2
TCGA-V3-A9ZY TCGA-V4-A9E5 TCGA-V4-A9E9 TCGA-V4-A9EC TCGA-V4-A9EH TCGA-V4-A9EJ 
        4.04        74.53        30.38        24.43        22.03        12.56 
TCGA-V4-A9EK TCGA-V4-A9EM TCGA-V4-A9EO TCGA-V4-A9ET TCGA-V4-A9EW TCGA-V4-A9EY 
       18.64        22.03        19.53        31.66        30.05        25.02 
TCGA-V4-A9EZ TCGA-V4-A9F4 TCGA-V4-A9F7 TCGA-VD-A8K7 TCGA-VD-A8KA TCGA-VD-AA8M 
       19.69        20.22        32.28         0.10        37.28         0.20 
TCGA-VD-AA8Q TCGA-VD-AA8S TCGA-WC-A87T TCGA-WC-A87U TCGA-WC-A87W TCGA-WC-A880 
        0.23        14.04        70.65        51.98        45.57        31.99 
TCGA-WC-A881 TCGA-WC-A885 TCGA-YZ-A982 TCGA-YZ-A985 
       22.82        10.36        16.27        25.81 

$subtype3
TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9F2 TCGA-V4-A9F5 TCGA-VD-A8K8 TCGA-VD-A8K9 
       14.96        37.81        12.20         6.67        16.87         0.46 
TCGA-VD-A8KB TCGA-VD-A8KD TCGA-VD-A8KE TCGA-VD-A8KF TCGA-VD-AA8P TCGA-VD-AA8T 
       35.31         3.75        26.99         1.32         2.83         0.49 
TCGA-WC-AA9A TCGA-WC-AA9E 
       14.89        14.20 

subtype1 subtype2 subtype3 
    0.13     0.10     0.46 
subtype1 subtype2 subtype3 
   52.64    74.53    37.81 
subtype1 subtype2 subtype3 
  13.430   22.425   13.200 
[1] "0.1 - 52.6 (13.4)" "0.1 - 74.5 (22.4)" "0.5 - 37.8 (13.2)"
D7V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         1        12         11          4          1        2
  subtype2         4        10         10          4          0        0
  subtype3         5         3          3          1          0        2
D7V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE IIA         1        4        5
  STAGE IIB        12       10        3
  STAGE IIIA       11       10        3
  STAGE IIIB        4        4        1
  STAGE IIIC        1        0        0
  STAGE IV          2        0        2
[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  3 14 15
  subtype2  4 11 13
  subtype3  5  5  4
D7V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T2        3        4        5
  T3       14       11        5
  T4       15       13        4
[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"
D7V5, binary
          cls
clus        0  1
  subtype1 20  2
  subtype2 23  0
  subtype3  5  2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   20    2
  subtype2   23    0
  subtype3    5    2
   clus
vv  subtype1 subtype2 subtype3
  0       20       23        5
  1        2        0        2
[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"
D7V6, binary
          cls
clus        0  1
  subtype1 12 20
  subtype2 10 18
  subtype3 10  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   12   20
  subtype2   10   18
  subtype3   10    4
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       12       10       10
  MALE         20       18        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"

Clustering(8) Variable = MIRSEQ_MATURE_CHIERARCHICAL
D8V1, survival
          sevent
clus2       0  1
  subtype1  3  2
  subtype2 12  0
  subtype3 16  0
  subtype4 15  1
  subtype5  9  6
  subtype6  6  4
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
       5       12       16       16       15       10 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
       2        0        0        1        6        4 
$subtype1
TCGA-RZ-AB0B TCGA-V4-A9EU TCGA-V4-A9F3 TCGA-VD-AA8N TCGA-WC-A883 
        4.90        23.31        22.03         1.45         7.92 

$subtype2
TCGA-V3-A9ZX TCGA-V4-A9EM TCGA-V4-A9F8 TCGA-VD-A8KH TCGA-VD-A8KJ TCGA-VD-A8KL 
        4.50        22.03        19.63         0.33        31.59        20.98 
TCGA-WC-A87Y TCGA-WC-A882 TCGA-WC-A884 TCGA-YZ-A980 TCGA-YZ-A982 TCGA-YZ-A984 
       31.40        11.31         0.39        52.64        16.27        42.08 

$subtype3
TCGA-V3-A9ZY TCGA-V4-A9E9 TCGA-V4-A9EC TCGA-V4-A9EH TCGA-V4-A9EJ TCGA-V4-A9EO 
        4.04        30.38        24.43        22.03        12.56        19.53 
TCGA-V4-A9EW TCGA-V4-A9EY TCGA-VD-A8K7 TCGA-VD-AA8Q TCGA-VD-AA8T TCGA-WC-A87T 
       30.05        25.02         0.10         0.23         0.49        70.65 
TCGA-WC-A87W TCGA-WC-A880 TCGA-WC-A885 TCGA-YZ-A985 
       45.57        31.99        10.36        25.81 

$subtype4
TCGA-V4-A9E5 TCGA-V4-A9EK TCGA-V4-A9ET TCGA-V4-A9EZ TCGA-V4-A9F2 TCGA-V4-A9F4 
       74.53        18.64        31.66        19.69        12.20        20.22 
TCGA-V4-A9F7 TCGA-VD-A8K9 TCGA-VD-A8KA TCGA-VD-A8KB TCGA-VD-A8KE TCGA-VD-AA8M 
       32.28         0.46        37.28        35.31        26.99         0.20 
TCGA-VD-AA8S TCGA-WC-A87U TCGA-WC-A881 TCGA-WC-AA9E 
       14.04        51.98        22.82        14.20 

$subtype5
TCGA-V4-A9E7 TCGA-V4-A9EE TCGA-V4-A9EQ TCGA-V4-A9ES TCGA-V4-A9EV TCGA-V4-A9F1 
       13.64        13.08        14.96        37.81        27.48        21.73 
TCGA-V4-A9F5 TCGA-VD-A8K8 TCGA-VD-A8KD TCGA-VD-A8KF TCGA-VD-A8KM TCGA-VD-AA8O 
        6.67        16.87         3.75         1.32         0.13         7.50 
TCGA-VD-AA8P TCGA-WC-A888 TCGA-WC-AA9A 
        2.83        10.13        14.89 

$subtype6
TCGA-V4-A9E8 TCGA-V4-A9ED TCGA-V4-A9EI TCGA-V4-A9EL TCGA-V4-A9EX TCGA-V4-A9F0 
       26.56        28.41        13.22        23.44        24.00        24.10 
TCGA-VD-A8KI TCGA-VD-A8KK TCGA-VD-A8KN TCGA-WC-A88A 
        1.25         2.10         2.24         2.70 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
    1.45     0.33     0.10     0.20     0.13     1.25 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
   23.31    52.64    70.65    74.53    37.81    28.41 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 
   7.920   20.305   23.230   21.520   13.080   18.330 
[1] "1.4 - 23.3 (7.9)"  "0.3 - 52.6 (20.3)" "0.1 - 70.7 (23.2)"
[4] "0.2 - 74.5 (21.5)" "0.1 - 37.8 (13.1)" "1.2 - 28.4 (18.3)"
D8V2, continuous
          vv
clus       STAGE IIA STAGE IIB STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1         0         1          2          0          1        1
  subtype2         0         5          3          3          0        0
  subtype3         3         5          7          1          0        0
  subtype4         5         6          3          2          0        0
  subtype5         1         7          4          1          0        2
  subtype6         1         1          5          2          0        1
D8V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  STAGE IIA         0        0        3        5        1        1
  STAGE IIB         1        5        5        6        7        1
  STAGE IIIA        2        3        7        3        4        5
  STAGE IIIB        0        3        1        2        1        2
  STAGE IIIC        1        0        0        0        0        0
  STAGE IV          1        0        0        0        2        1
[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  0  2  3
  subtype2  2  5  5
  subtype3  3  5  8
  subtype4  5  8  3
  subtype5  1  8  6
  subtype6  1  2  7
D8V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  T2        0        2        3        5        1        1
  T3        2        5        5        8        8        2
  T4        3        5        8        3        6        7
[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"
D8V5, binary
          cls
clus        0  1
  subtype1  4  1
  subtype2  5  0
  subtype3 13  0
  subtype4 11  0
  subtype5  9  2
  subtype6  6  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    4    1
  subtype2    5    0
  subtype3   13    0
  subtype4   11    0
  subtype5    9    2
  subtype6    6    1
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  0        4        5       13       11        9        6
  1        1        0        0        0        2        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"
D8V6, binary
          cls
clus        0  1
  subtype1  4  1
  subtype2  5  7
  subtype3  6 10
  subtype4  8  8
  subtype5  7  8
  subtype6  2  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    4    1
  subtype2    5    7
  subtype3    6   10
  subtype4    8    8
  subtype5    7    8
  subtype6    2    8
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6
  FEMALE        4        5        6        8        7        2
  MALE          1        7       10        8        8        8
[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"
