[1] "ofn"       "-oTACC-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/ACC-TP/15074660/ACC-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/ACC-TP/15087341/ACC-TP.mergedcluster.txt"

nPatients in clinical file=92, in cluster file=92, common to both=92
[1] 10 92
[1] "CN_CNMF"
[1] 3
 1  2  3  4 
36 26 16 12 
 1  2  3  4 
36 26 16 12 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3  4  5 
18 11 22 18 11 
 1  2  3  4  5 
18 11 22 18 11 
[1] "RPPA_CNMF"
[1] 3
 1  2 
22 24 
 1  2 
22 24 
[1] "RPPA_CHIERARCHICAL"
[1] 3
1 2 3 4 5 6 7 8 
8 7 7 3 4 4 7 6 
1 2 3 4 5 6 7 8 
8 7 7 3 4 4 7 6 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2  3  4 
24 14 18 23 
 1  2  3  4 
24 14 18 23 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
 1  2  3  4 
23 24  7 25 
 1  2  3  4 
23 24  7 25 
[1] "MIRSEQ_CNMF"
[1] 3
 1  2  3 
38 16 26 
 1  2  3 
38 16 26 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
 1  2  3  4  5 
17 27 12 20  4 
 1  2  3  4  5 
17 27 12 20  4 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
 1  2  3 
29 22 27 
 1  2  3 
29 22 27 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
 1  2  3 
40 24 14 
 1  2  3 
40 24 14 
[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] "RADIATION_THERAPY"                     
[12] "RADIATIONS_RADIATION_REGIMENINDICATION"
[13] "RACE"                                  
[14] "ETHNICITY"                             
[15] "BATCH_NUMBER"                          

Input Data has 15 rows and 92 columns.

[1] "Batch" "15"   
[1] "Last Follow UP"
Variable 1:'YEARS_TO_BIRTH':	nDistinctValues=50,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 2:'VITAL_STATUS':	nDistinctValues=2,	numeric=TRUE,	binary=TRUE,	exclude=FALSE.
Variable 3:'DAYS_TO_DEATH':	nDistinctValues=32,	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=61,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
[1] "exclude grep('FOLLOWUP', vnms) to deal with survival parameters seperately"
Variable 5:'NEOPLASM_DISEASESTAGE':	nDistinctValues=4,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 6:'PATHOLOGY_T_STAGE':	nDistinctValues=4,	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=0,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "PATHOLOGY_M_STAGE is excluded in the analysis because there is no more than two cases of (unique non-NA values)"
Variable 9:'DCC_UPLOAD_DATE':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "DCC_UPLOAD_DATE is excluded in the analysis because there is no more than two cases of (unique non-NA values)"
Variable 10:'GENDER':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 11:'RADIATION_THERAPY':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "RADIATION_THERAPY is excluded in the analysis because there is no more than two cases of (unique non-NA values)"
Variable 12:'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 13:'RACE':	nDistinctValues=3,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 14:'ETHNICITY':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 15:'BATCH_NUMBER':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] NA
[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] "****** SUMMARY ***** "
Output Data has 92 columns, 1 survival variables, and 7 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_N_STAGE"     "GENDER"                "RACE"                 
[7] "ETHNICITY"            
YEARS_TO_BIRTH, nv=50, binary=FALSE, numeric=TRUE
NEOPLASM_DISEASESTAGE, nv=4, binary=FALSE, numeric=FALSE
PATHOLOGY_T_STAGE, nv=4, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.T',vnm)"
vv
T1 T2 T3 T4 
 9 49 11 21 
[1] "table(vv)"
vv
T1 T2 T3 T4 
 9 49 11 21 
$ClinVariableName
[1] "PATHOLOGY_T_STAGE"

$Table
vv
T1 T2 T3 T4 
 9 49 11 21 

$nClasses
[1] 4

$ClinVariableType
[1] "multiclass(4)"


T1 T2 T3 T4 
 9 49 11 21 
PATHOLOGY_N_STAGE, nv=2, binary=FALSE, numeric=TRUE
GENDER, nv=2, binary=FALSE, numeric=FALSE
RACE, nv=3, binary=FALSE, numeric=FALSE
ETHNICITY, nv=2, binary=FALSE, numeric=FALSE

Clustering(1) Variable = CN_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 18 18
  subtype2 23  3
  subtype3  7  9
  subtype4 10  2
subtype1 subtype2 subtype3 subtype4 
      36       26       16       12 
subtype1 subtype2 subtype3 subtype4 
      18        3        9        2 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J2 TCGA-OR-A5J6 TCGA-OR-A5J8 TCGA-OR-A5JB TCGA-OR-A5JE 
       44.55        55.13        88.87        19.04        18.12        69.21 
TCGA-OR-A5JM TCGA-OR-A5JO TCGA-OR-A5JP TCGA-OR-A5JS TCGA-OR-A5JU TCGA-OR-A5JV 
       18.48        29.23        15.25        12.59         9.50        66.51 
TCGA-OR-A5JY TCGA-OR-A5K0 TCGA-OR-A5K2 TCGA-OR-A5K5 TCGA-OR-A5K6 TCGA-OR-A5K9 
       18.15        33.83        32.68        16.37        49.08        11.31 
TCGA-OR-A5KB TCGA-OR-A5KP TCGA-OR-A5KQ TCGA-OR-A5KT TCGA-OR-A5KV TCGA-OR-A5L2 
       24.36        91.30        88.01        95.18       127.50        60.89 
TCGA-OR-A5L3 TCGA-OR-A5LD TCGA-OR-A5LE TCGA-OR-A5LG TCGA-OR-A5LI TCGA-OR-A5LL 
      152.15        39.35        21.76        52.24        14.33        53.03 
TCGA-P6-A5OG TCGA-P6-A5OH TCGA-PK-A5H9 TCGA-PK-A5HA TCGA-PK-A5HB TCGA-PK-A5HC 
       12.59         0.00        20.25        39.48        42.51        22.32 

$subtype2
TCGA-OR-A5J3 TCGA-OR-A5JF TCGA-OR-A5JJ TCGA-OR-A5JK TCGA-OR-A5JR TCGA-OR-A5JT 
       68.75        66.25        16.11        49.22       121.25        29.82 
TCGA-OR-A5JX TCGA-OR-A5JZ TCGA-OR-A5K1 TCGA-OR-A5K3 TCGA-OR-A5K4 TCGA-OR-A5KS 
       31.23        27.02        96.59       100.18        22.98        83.80 
TCGA-OR-A5KU TCGA-OR-A5KW TCGA-OR-A5L1 TCGA-OR-A5L4 TCGA-OR-A5L5 TCGA-OR-A5L6 
      153.63        50.37        58.55        31.79        43.30        28.31 
TCGA-OR-A5L8 TCGA-OR-A5L9 TCGA-OR-A5LA TCGA-OR-A5LC TCGA-OR-A5LF TCGA-OR-A5LP 
       29.10        28.64        23.64         5.23        14.63        61.05 
TCGA-OR-A5LR TCGA-PA-A5YG 
       28.04        24.85 

$subtype3
TCGA-OR-A5J4 TCGA-OR-A5J5 TCGA-OR-A5J7 TCGA-OR-A5J9 TCGA-OR-A5JA TCGA-OR-A5JC 
       13.91        12.00        16.11        44.45        30.31        57.53 
TCGA-OR-A5JG TCGA-OR-A5K8 TCGA-OR-A5KX TCGA-OR-A5KY TCGA-OR-A5LB TCGA-OR-A5LJ 
       17.79        24.62        44.84        12.85        39.58        36.33 
TCGA-OR-A5LM TCGA-OR-A5LO TCGA-OR-A5LS TCGA-OU-A5PI 
       61.08        69.11        36.03        38.50 

$subtype4
TCGA-OR-A5JD TCGA-OR-A5JH TCGA-OR-A5JI TCGA-OR-A5JL TCGA-OR-A5JQ TCGA-OR-A5JW 
       91.46        69.37        46.82        22.03        36.26        72.39 
TCGA-OR-A5KO TCGA-OR-A5KZ TCGA-OR-A5LH TCGA-OR-A5LK TCGA-OR-A5LN TCGA-OR-A5LT 
       46.49         4.11        78.41        73.05        62.99        18.05 

subtype1 subtype2 subtype3 subtype4 
    0.00     5.23    12.00     4.11 
subtype1 subtype2 subtype3 subtype4 
  152.15   153.63    69.11    91.46 
subtype1 subtype2 subtype3 subtype4 
  33.255   31.510   36.180   54.905 
[1] "0.0 - 152.2 (33.3)" "5.2 - 153.6 (31.5)" "12.0 - 69.1 (36.2)"
[4] "4.1 - 91.5 (54.9)" 
D1V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       5       15         8        7
  subtype2       2       15         6        3
  subtype3       0        5         3        7
  subtype4       2        8         1        1
D1V3, multiclass
           clus
vv          subtype1 subtype2 subtype3 subtype4
  STAGE I          5        2        0        2
  STAGE II        15       15        5        8
  STAGE III        8        6        3        1
  STAGE IV         7        3        7        1
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  5 16  5  9
  subtype2  2 16  3  5
  subtype3  0  8  2  5
  subtype4  2  8  1  1
D1V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  T1        5        2        0        2
  T2       16       16        8        8
  T3        5        3        2        1
  T4        9        5        5        1
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V5, binary
          cls
clus        0  1
  subtype1 33  2
  subtype2 24  2
  subtype3  9  6
  subtype4 12  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   33    2
  subtype2   24    2
  subtype3    9    6
  subtype4   12    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       33       24        9       12
  1        2        2        6        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"
D1V6, binary
          cls
clus        0  1
  subtype1 26 10
  subtype2 16 10
  subtype3 10  6
  subtype4  7  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   26   10
  subtype2   16   10
  subtype3   10    6
  subtype4    7    5
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       26       16       10        7
  MALE         10       10        6        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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     2                         1    30
  subtype2     0                         0    24
  subtype3     0                         0    13
  subtype4     0                         0     9
D1V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            2        0        0        0
  BLACK OR AFRICAN AMERICAN        1        0        0        0
  WHITE                           30       24       13        9
[1] 3 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D1V8, binary
          cls
clus        0  1
  subtype1  3 16
  subtype2  1 13
  subtype3  4  6
  subtype4  0  3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   16
  subtype2    1   13
  subtype3    4    6
  subtype4    0    3
                        clus
vv                       subtype1 subtype2 subtype3 subtype4
  HISPANIC OR LATINO            3        1        4        0
  NOT HISPANIC OR LATINO       16       13        6        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"

Clustering(2) Variable = METHLYATION_CNMF
D2V1, survival
          sevent
clus2       0  1
  subtype1  5 13
  subtype2  8  3
  subtype3 14  8
  subtype4 15  3
  subtype5 10  1
subtype1 subtype2 subtype3 subtype4 subtype5 
      18       11       22       18       11 
subtype1 subtype2 subtype3 subtype4 subtype5 
      13        3        8        3        1 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J4 TCGA-OR-A5J7 TCGA-OR-A5J9 TCGA-OR-A5JE TCGA-OR-A5JM 
       44.55        13.91        16.11        44.45        69.21        18.48 
TCGA-OR-A5JP TCGA-OR-A5JY TCGA-OR-A5K0 TCGA-OR-A5K2 TCGA-OR-A5K5 TCGA-OR-A5K9 
       15.25        18.15        33.83        32.68        16.37        11.31 
TCGA-OR-A5KV TCGA-OR-A5KX TCGA-OR-A5KZ TCGA-OR-A5LC TCGA-OR-A5LD TCGA-OR-A5LE 
      127.50        44.84         4.11         5.23        39.35        21.76 

$subtype2
TCGA-OR-A5J2 TCGA-OR-A5J3 TCGA-OR-A5JF TCGA-OR-A5K6 TCGA-OR-A5KO TCGA-OR-A5KW 
       55.13        68.75        66.25        49.08        46.49        50.37 
TCGA-OR-A5L3 TCGA-OR-A5LG TCGA-OR-A5LJ TCGA-OR-A5LL TCGA-OR-A5LT 
      152.15        52.24        36.33        53.03        18.05 

$subtype3
TCGA-OR-A5J5 TCGA-OR-A5JA TCGA-OR-A5JC TCGA-OR-A5JG TCGA-OR-A5JI TCGA-OR-A5JJ 
       12.00        30.31        57.53        17.79        46.82        16.11 
TCGA-OR-A5JW TCGA-OR-A5JX TCGA-OR-A5K3 TCGA-OR-A5K8 TCGA-OR-A5KU TCGA-OR-A5KY 
       72.39        31.23       100.18        24.62       153.63        12.85 
TCGA-OR-A5L6 TCGA-OR-A5LB TCGA-OR-A5LM TCGA-OR-A5LO TCGA-OR-A5LS TCGA-OU-A5PI 
       28.31        39.58        61.08        69.11        36.03        38.50 
TCGA-P6-A5OF TCGA-PK-A5H8 TCGA-PK-A5HA TCGA-PK-A5HB 
        6.81       119.11        39.48        42.51 

$subtype4
TCGA-OR-A5J6 TCGA-OR-A5J8 TCGA-OR-A5JB TCGA-OR-A5JK TCGA-OR-A5JO TCGA-OR-A5JR 
       88.87        19.04        18.12        49.22        29.23       121.25 
TCGA-OR-A5JT TCGA-OR-A5JV TCGA-OR-A5JZ TCGA-OR-A5K1 TCGA-OR-A5K4 TCGA-OR-A5KT 
       29.82        66.51        27.02        96.59        22.98        95.18 
TCGA-OR-A5L4 TCGA-OR-A5L9 TCGA-OR-A5LK TCGA-P6-A5OG TCGA-PA-A5YG TCGA-PK-A5H9 
       31.79        28.64        73.05        12.59        24.85        20.25 

$subtype5
TCGA-OR-A5JD TCGA-OR-A5JL TCGA-OR-A5JQ TCGA-OR-A5JS TCGA-OR-A5L5 TCGA-OR-A5L8 
       91.46        22.03        36.26        12.59        43.30        29.10 
TCGA-OR-A5LA TCGA-OR-A5LH TCGA-OR-A5LN TCGA-OR-A5LP TCGA-OR-A5LR 
       23.64        78.41        62.99        61.05        28.04 

subtype1 subtype2 subtype3 subtype4 subtype5 
    4.11    18.05     6.81    12.59    12.59 
subtype1 subtype2 subtype3 subtype4 subtype5 
  127.50   152.15   153.63   121.25    91.46 
subtype1 subtype2 subtype3 subtype4 subtype5 
  20.120   52.240   38.990   29.525   36.260 
[1] "4.1 - 127.5 (20.1)"  "18.1 - 152.2 (52.2)" "6.8 - 153.6 (39.0)" 
[4] "12.6 - 121.2 (29.5)" "12.6 - 91.5 (36.3)" 
D2V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       1        7         6        4
  subtype2       1        3         4        3
  subtype3       2        9         3        6
  subtype4       3        9         3        3
  subtype5       2        9         0        0
D2V3, multiclass
           clus
vv          subtype1 subtype2 subtype3 subtype4 subtype5
  STAGE I          1        1        2        3        2
  STAGE II         7        3        9        9        9
  STAGE III        6        4        3        3        0
  STAGE IV         4        3        6        3        0
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  1  9  3  5
  subtype2  1  5  4  1
  subtype3  2 10  1  7
  subtype4  3  9  1  5
  subtype5  2  9  0  0
D2V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5
  T1        1        1        2        3        2
  T2        9        5       10        9        9
  T3        3        4        1        1        0
  T4        5        1        7        5        0
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V5, binary
          cls
clus        0  1
  subtype1 14  4
  subtype2  9  2
  subtype3 16  4
  subtype4 18  0
  subtype5 11  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   14    4
  subtype2    9    2
  subtype3   16    4
  subtype4   18    0
  subtype5   11    0
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5
  0       14        9       16       18       11
  1        4        2        4        0        0
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V6, binary
          cls
clus        0  1
  subtype1 13  5
  subtype2  9  2
  subtype3  7 15
  subtype4  9  9
  subtype5 11  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   13    5
  subtype2    9    2
  subtype3    7   15
  subtype4    9    9
  subtype5   11    0
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5
  FEMALE       13        9        7        9       11
  MALE          5        2       15        9        0
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    18
  subtype2     0                         0     9
  subtype3     0                         0    17
  subtype4     1                         1    15
  subtype5     0                         0     8
D2V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            0        0        0        1        0
  BLACK OR AFRICAN AMERICAN        0        0        0        1        0
  WHITE                           18        9       17       15        8
[1] 3 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D2V8, binary
          cls
clus       0 1
  subtype1 3 6
  subtype2 2 6
  subtype3 1 8
  subtype4 2 6
  subtype5 0 4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3    6
  subtype2    2    6
  subtype3    1    8
  subtype4    2    6
  subtype5    0    4
                        clus
vv                       subtype1 subtype2 subtype3 subtype4 subtype5
  HISPANIC OR LATINO            3        2        1        2        0
  NOT HISPANIC OR LATINO        6        6        8        6        4
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(3) Variable = RPPA_CNMF
D3V1, survival
          sevent
clus2       0  1
  subtype1 18  4
  subtype2 15  9
subtype1 subtype2 
      22       24 
subtype1 subtype2 
       4        9 
$subtype1
TCGA-OR-A5J2 TCGA-OR-A5J6 TCGA-OR-A5JR TCGA-OR-A5JT TCGA-OR-A5JV TCGA-OR-A5JY 
       55.13        88.87       121.25        29.82        66.51        18.15 
TCGA-OR-A5JZ TCGA-OR-A5K1 TCGA-OR-A5K3 TCGA-OR-A5K4 TCGA-OR-A5KU TCGA-OR-A5KX 
       27.02        96.59       100.18        22.98       153.63        44.84 
TCGA-OR-A5LH TCGA-OR-A5LK TCGA-OR-A5LN TCGA-OR-A5LP TCGA-OR-A5LS TCGA-P6-A5OG 
       78.41        73.05        62.99        61.05        36.03        12.59 
TCGA-PA-A5YG TCGA-PK-A5H8 TCGA-PK-A5H9 TCGA-PK-A5HA 
       24.85       119.11        20.25        39.48 

$subtype2
TCGA-OR-A5J3 TCGA-OR-A5J7 TCGA-OR-A5J8 TCGA-OR-A5J9 TCGA-OR-A5JA TCGA-OR-A5JP 
       68.75        16.11        19.04        44.45        30.31        15.25 
TCGA-OR-A5JS TCGA-OR-A5JW TCGA-OR-A5K0 TCGA-OR-A5K5 TCGA-OR-A5K6 TCGA-OR-A5K8 
       12.59        72.39        33.83        16.37        49.08        24.62 
TCGA-OR-A5KO TCGA-OR-A5KW TCGA-OR-A5KY TCGA-OR-A5KZ TCGA-OR-A5LD TCGA-OR-A5LG 
       46.49        50.37        12.85         4.11        39.35        52.24 
TCGA-OR-A5LJ TCGA-OR-A5LL TCGA-OR-A5LM TCGA-OR-A5LO TCGA-OR-A5LT TCGA-OU-A5PI 
       36.33        53.03        61.08        69.11        18.05        38.50 

subtype1 subtype2 
   12.59     4.11 
subtype1 subtype2 
  153.63    72.39 
subtype1 subtype2 
  58.090   37.415 
[1] "12.6 - 153.6 (58.1)" "4.1 - 72.4 (37.4)"  
[1] "hr=" "3.8"
D3V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       2       15         2        3
  subtype2       0       11         8        5
D3V3, multiclass
           clus
vv          subtype1 subtype2
  STAGE I          2        0
  STAGE II        15       11
  STAGE III        2        8
  STAGE IV         3        5
[1] 4 2
[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       T1 T2 T3 T4
  subtype1  2 16  1  3
  subtype2  0 14  6  4
D3V4, multiclass
    clus
vv   subtype1 subtype2
  T1        2        0
  T2       16       14
  T3        1        6
  T4        3        4
[1] 4 2
[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 20  2
  subtype2 20  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   20    2
  subtype2   20    4
   clus
vv  subtype1 subtype2
  0       20       20
  1        2        4
[1] 2 2
[1] FALSE
D3V6, binary
          cls
clus        0  1
  subtype1 13  9
  subtype2 15  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   13    9
  subtype2   15    9
        clus
vv       subtype1 subtype2
  FEMALE       13       15
  MALE          9        9
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         1    15
  subtype2     0                         0    20
D3V7, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            1        0
  BLACK OR AFRICAN AMERICAN        1        0
  WHITE                           15       20
[1] 3 2
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D3V8, binary
          cls
clus        0  1
  subtype1  2  7
  subtype2  4 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2    7
  subtype2    4   10
                        clus
vv                       subtype1 subtype2
  HISPANIC OR LATINO            2        4
  NOT HISPANIC OR LATINO        7       10
[1] 2 2
[1] FALSE

Clustering(4) Variable = RPPA_CHIERARCHICAL
D4V1, survival
          sevent
clus2      0 1
  subtype1 4 4
  subtype2 4 3
  subtype3 7 0
  subtype4 2 1
  subtype5 1 3
  subtype6 4 0
  subtype7 6 1
  subtype8 5 1
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8 
       8        7        7        3        4        4        7        6 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8 
       4        3        0        1        3        0        1        1 
$subtype1
TCGA-OR-A5J2 TCGA-OR-A5J9 TCGA-OR-A5K0 TCGA-OR-A5KZ TCGA-OR-A5LD TCGA-OR-A5LJ 
       55.13        44.45        33.83         4.11        39.35        36.33 
TCGA-OR-A5LO TCGA-OR-A5LS 
       69.11        36.03 

$subtype2
TCGA-OR-A5J3 TCGA-OR-A5JA TCGA-OR-A5K5 TCGA-OR-A5K8 TCGA-OR-A5KO TCGA-OR-A5KW 
       68.75        30.31        16.37        24.62        46.49        50.37 
TCGA-OR-A5KY 
       12.85 

$subtype3
TCGA-OR-A5J6 TCGA-OR-A5JT TCGA-OR-A5JZ TCGA-OR-A5LK TCGA-OR-A5LP TCGA-PA-A5YG 
       88.87        29.82        27.02        73.05        61.05        24.85 
TCGA-PK-A5HA 
       39.48 

$subtype4
TCGA-OR-A5J7 TCGA-OR-A5JP TCGA-OR-A5KX 
       16.11        15.25        44.84 

$subtype5
TCGA-OR-A5J8 TCGA-OR-A5JY TCGA-OR-A5KU TCGA-P6-A5OG 
       19.04        18.15       153.63        12.59 

$subtype6
TCGA-OR-A5JR TCGA-OR-A5K1 TCGA-OR-A5LN TCGA-OR-A5LT 
      121.25        96.59        62.99        18.05 

$subtype7
TCGA-OR-A5JS TCGA-OR-A5JV TCGA-OR-A5K3 TCGA-OR-A5K4 TCGA-OR-A5LH TCGA-OR-A5LM 
       12.59        66.51       100.18        22.98        78.41        61.08 
TCGA-PK-A5H8 
      119.11 

$subtype8
TCGA-OR-A5JW TCGA-OR-A5K6 TCGA-OR-A5LG TCGA-OR-A5LL TCGA-OU-A5PI TCGA-PK-A5H9 
       72.39        49.08        52.24        53.03        38.50        20.25 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8 
    4.11    12.85    24.85    15.25    12.59    18.05    12.59    20.25 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8 
   69.11    68.75    88.87    44.84   153.63   121.25   119.11    72.39 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8 
  37.840   30.310   39.480   16.110   18.595   79.790   66.510   50.660 
[1] "4.1 - 69.1 (37.8)"   "12.8 - 68.8 (30.3)"  "24.9 - 88.9 (39.5)" 
[4] "15.2 - 44.8 (16.1)"  "12.6 - 153.6 (18.6)" "18.1 - 121.2 (79.8)"
[7] "12.6 - 119.1 (66.5)" "20.2 - 72.4 (50.7)" 
D4V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       0        5         1        2
  subtype2       0        1         3        3
  subtype3       1        6         0        0
  subtype4       0        1         2        0
  subtype5       0        1         1        2
  subtype6       1        2         1        0
  subtype7       0        6         1        0
  subtype8       0        4         1        1
D4V3, multiclass
           clus
vv          subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  STAGE I          0        0        1        0        0        1        0
  STAGE II         5        1        6        1        1        2        6
  STAGE III        1        3        0        2        1        1        1
  STAGE IV         2        3        0        0        2        0        0
           clus
vv          subtype8
  STAGE I          0
  STAGE II         4
  STAGE III        1
  STAGE IV         1
[1] 4 8
[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       T1 T2 T3 T4
  subtype1  0  6  1  1
  subtype2  0  2  2  3
  subtype3  1  6  0  0
  subtype4  0  2  1  0
  subtype5  0  1  1  2
  subtype6  1  2  1  0
  subtype7  0  6  0  1
  subtype8  0  5  1  0
D4V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8
  T1        0        0        1        0        0        1        0        0
  T2        6        2        6        2        1        2        6        5
  T3        1        2        0        1        1        1        0        1
  T4        1        3        0        0        2        0        1        0
[1] 4 8
[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 7 1
  subtype2 5 2
  subtype3 7 0
  subtype4 2 1
  subtype5 3 1
  subtype6 4 0
  subtype7 7 0
  subtype8 5 1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7    1
  subtype2    5    2
  subtype3    7    0
  subtype4    2    1
  subtype5    3    1
  subtype6    4    0
  subtype7    7    0
  subtype8    5    1
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8
  0        7        5        7        2        3        4        7        5
  1        1        2        0        1        1        0        0        1
[1] 2 8
[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 6 2
  subtype2 6 1
  subtype3 3 4
  subtype4 2 1
  subtype5 3 1
  subtype6 1 3
  subtype7 3 4
  subtype8 4 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    6    2
  subtype2    6    1
  subtype3    3    4
  subtype4    2    1
  subtype5    3    1
  subtype6    1    3
  subtype7    3    4
  subtype8    4    2
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  FEMALE        6        6        3        2        3        1        3
  MALE          2        1        4        1        1        3        4
        clus
vv       subtype8
  FEMALE        4
  MALE          2
[1] 2 8
[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       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0     6
  subtype2     0                         0     7
  subtype3     0                         1     3
  subtype4     0                         0     3
  subtype5     0                         0     4
  subtype6     0                         0     2
  subtype7     0                         0     6
  subtype8     1                         0     4
D4V7, multiclass
[1] "Remove cluster labels:" "subtype6"              
clus
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 subtype8 
       6        7        4        3        4        2        6        5 
 [1] "subtype1" "subtype2" "subtype3" "subtype4" "subtype5" "subtype1"
 [7] "subtype2" "subtype4" "subtype7" "subtype3" "subtype7" "subtype8"
[13] "subtype5" "subtype3" "subtype1" "subtype7" "subtype7" "subtype2"
[19] "subtype8" "subtype2" "subtype2" "subtype5" "subtype2" "subtype4"
[25] "subtype2" "subtype1" "subtype1" "subtype8" "subtype7" "subtype1"
[31] "subtype8" "subtype5" "subtype3" "subtype7" "subtype8"
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            0        0        0        0        0
  BLACK OR AFRICAN AMERICAN        0        0        1        0        0
  WHITE                            6        7        3        3        4
                           clus
vv                          subtype7 subtype8
  ASIAN                            0        1
  BLACK OR AFRICAN AMERICAN        0        0
  WHITE                            6        4
[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"
D4V8, binary
          cls
clus       0 1
  subtype1 2 3
  subtype2 1 4
  subtype3 1 1
  subtype4 1 1
  subtype5 1 2
  subtype6 0 0
  subtype7 0 2
  subtype8 0 4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2    3
  subtype2    1    4
  subtype3    1    1
  subtype4    1    1
  subtype5    1    2
  subtype6    0    0
  subtype7    0    2
  subtype8    0    4
                        clus
vv                       subtype1 subtype2 subtype3 subtype4 subtype5 subtype7
  HISPANIC OR LATINO            2        1        1        1        1        0
  NOT HISPANIC OR LATINO        3        4        1        1        2        2
                        clus
vv                       subtype8
  HISPANIC OR LATINO            0
  NOT HISPANIC OR LATINO        4
[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(5) Variable = MRNASEQ_CNMF
D5V1, survival
          sevent
clus2       0  1
  subtype1  9 15
  subtype2  8  6
  subtype3 13  5
  subtype4 22  1
subtype1 subtype2 subtype3 subtype4 
      24       14       18       23 
subtype1 subtype2 subtype3 subtype4 
      15        6        5        1 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J7 TCGA-OR-A5J8 TCGA-OR-A5JB TCGA-OR-A5JE TCGA-OR-A5JM 
       44.55        16.11        19.04        18.12        69.21        18.48 
TCGA-OR-A5JP TCGA-OR-A5JS TCGA-OR-A5JY TCGA-OR-A5K0 TCGA-OR-A5K2 TCGA-OR-A5K5 
       15.25        12.59        18.15        33.83        32.68        16.37 
TCGA-OR-A5K6 TCGA-OR-A5K9 TCGA-OR-A5KT TCGA-OR-A5KV TCGA-OR-A5KX TCGA-OR-A5KZ 
       49.08        11.31        95.18       127.50        44.84         4.11 
TCGA-OR-A5L3 TCGA-OR-A5LC TCGA-OR-A5LD TCGA-OR-A5LE TCGA-OR-A5LG TCGA-P6-A5OG 
      152.15         5.23        39.35        21.76        52.24        12.59 

$subtype2
TCGA-OR-A5J2 TCGA-OR-A5J9 TCGA-OR-A5JF TCGA-OR-A5JJ TCGA-OR-A5JX TCGA-OR-A5KU 
       55.13        44.45        66.25        16.11        31.23       153.63 
TCGA-OR-A5KY TCGA-OR-A5L8 TCGA-OR-A5LB TCGA-OR-A5LJ TCGA-OR-A5LO TCGA-OR-A5LS 
       12.85        29.10        39.58        36.33        69.11        36.03 
TCGA-OU-A5PI TCGA-P6-A5OF 
       38.50         6.81 

$subtype3
TCGA-OR-A5J3 TCGA-OR-A5J5 TCGA-OR-A5JA TCGA-OR-A5JC TCGA-OR-A5JG TCGA-OR-A5JL 
       68.75        12.00        30.31        57.53        17.79        22.03 
TCGA-OR-A5JV TCGA-OR-A5JW TCGA-OR-A5K3 TCGA-OR-A5K4 TCGA-OR-A5K8 TCGA-OR-A5KO 
       66.51        72.39       100.18        22.98        24.62        46.49 
TCGA-OR-A5KW TCGA-OR-A5L4 TCGA-OR-A5LH TCGA-OR-A5LM TCGA-PK-A5H8 TCGA-PK-A5HB 
       50.37        31.79        78.41        61.08       119.11        42.51 

$subtype4
TCGA-OR-A5J6 TCGA-OR-A5JD TCGA-OR-A5JI TCGA-OR-A5JK TCGA-OR-A5JO TCGA-OR-A5JQ 
       88.87        91.46        46.82        49.22        29.23        36.26 
TCGA-OR-A5JR TCGA-OR-A5JT TCGA-OR-A5JZ TCGA-OR-A5K1 TCGA-OR-A5L5 TCGA-OR-A5L6 
      121.25        29.82        27.02        96.59        43.30        28.31 
TCGA-OR-A5L9 TCGA-OR-A5LA TCGA-OR-A5LK TCGA-OR-A5LL TCGA-OR-A5LN TCGA-OR-A5LP 
       28.64        23.64        73.05        53.03        62.99        61.05 
TCGA-OR-A5LR TCGA-OR-A5LT TCGA-PA-A5YG TCGA-PK-A5H9 TCGA-PK-A5HA 
       28.04        18.05        24.85        20.25        39.48 

subtype1 subtype2 subtype3 subtype4 
    4.11     6.81    12.00    18.05 
subtype1 subtype2 subtype3 subtype4 
  152.15   153.63   119.11   121.25 
subtype1 subtype2 subtype3 subtype4 
  20.400   37.415   48.430   39.480 
[1] "4.1 - 152.2 (20.4)"  "6.8 - 153.6 (37.4)"  "12.0 - 119.1 (48.4)"
[4] "18.1 - 121.2 (39.5)"
D5V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       3        8         8        5
  subtype2       0        6         2        6
  subtype3       1        7         5        3
  subtype4       5       16         1        1
D5V3, multiclass
           clus
vv          subtype1 subtype2 subtype3 subtype4
  STAGE I          3        0        1        5
  STAGE II         8        6        7       16
  STAGE III        8        2        5        1
  STAGE IV         5        6        3        1
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  3 10  4  7
  subtype2  0  8  2  4
  subtype3  1  8  1  6
  subtype4  5 16  1  1
D5V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  T1        3        0        1        5
  T2       10        8        8       16
  T3        4        2        1        1
  T4        7        4        6        1
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V5, binary
          cls
clus        0  1
  subtype1 21  3
  subtype2 10  4
  subtype3 14  2
  subtype4 23  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   21    3
  subtype2   10    4
  subtype3   14    2
  subtype4   23    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       21       10       14       23
  1        3        4        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"
D5V6, binary
          cls
clus        0  1
  subtype1 16  8
  subtype2 11  3
  subtype3  8 10
  subtype4 13 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   16    8
  subtype2   11    3
  subtype3    8   10
  subtype4   13   10
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       16       11        8       13
  MALE          8        3       10       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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    24
  subtype2     0                         0    12
  subtype3     0                         0    16
  subtype4     1                         1    14
D5V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            0        0        0        1
  BLACK OR AFRICAN AMERICAN        0        0        0        1
  WHITE                           24       12       16       14
[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"
D5V8, binary
          cls
clus        0  1
  subtype1  2 11
  subtype2  2  7
  subtype3  2  6
  subtype4  1  6
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   11
  subtype2    2    7
  subtype3    2    6
  subtype4    1    6
                        clus
vv                       subtype1 subtype2 subtype3 subtype4
  HISPANIC OR LATINO            2        2        2        1
  NOT HISPANIC OR LATINO       11        7        6        6
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(6) Variable = MRNASEQ_CHIERARCHICAL
D6V1, survival
          sevent
clus2       0  1
  subtype1  8 15
  subtype2 16  8
  subtype3  4  3
  subtype4 24  1
subtype1 subtype2 subtype3 subtype4 
      23       24        7       25 
subtype1 subtype2 subtype3 subtype4 
      15        8        3        1 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J2 TCGA-OR-A5J7 TCGA-OR-A5JE TCGA-OR-A5JM TCGA-OR-A5JP 
       44.55        55.13        16.11        69.21        18.48        15.25 
TCGA-OR-A5JS TCGA-OR-A5JY TCGA-OR-A5K0 TCGA-OR-A5K2 TCGA-OR-A5K5 TCGA-OR-A5K6 
       12.59        18.15        33.83        32.68        16.37        49.08 
TCGA-OR-A5K9 TCGA-OR-A5KV TCGA-OR-A5KX TCGA-OR-A5KZ TCGA-OR-A5L3 TCGA-OR-A5LC 
       11.31       127.50        44.84         4.11       152.15         5.23 
TCGA-OR-A5LD TCGA-OR-A5LE TCGA-OR-A5LG TCGA-OR-A5LJ TCGA-OR-A5LL 
       39.35        21.76        52.24        36.33        53.03 

$subtype2
TCGA-OR-A5J3 TCGA-OR-A5J5 TCGA-OR-A5J9 TCGA-OR-A5JA TCGA-OR-A5JC TCGA-OR-A5JF 
       68.75        12.00        44.45        30.31        57.53        66.25 
TCGA-OR-A5JG TCGA-OR-A5JJ TCGA-OR-A5JK TCGA-OR-A5JW TCGA-OR-A5JX TCGA-OR-A5K8 
       17.79        16.11        49.22        72.39        31.23        24.62 
TCGA-OR-A5KO TCGA-OR-A5KU TCGA-OR-A5KW TCGA-OR-A5KY TCGA-OR-A5L8 TCGA-OR-A5LB 
       46.49       153.63        50.37        12.85        29.10        39.58 
TCGA-OR-A5LM TCGA-OR-A5LO TCGA-OR-A5LS TCGA-OU-A5PI TCGA-P6-A5OF TCGA-PK-A5HB 
       61.08        69.11        36.03        38.50         6.81        42.51 

$subtype3
TCGA-OR-A5J6 TCGA-OR-A5J8 TCGA-OR-A5JB TCGA-OR-A5JO TCGA-OR-A5KT TCGA-P6-A5OG 
       88.87        19.04        18.12        29.23        95.18        12.59 
TCGA-PK-A5H9 
       20.25 

$subtype4
TCGA-OR-A5JD TCGA-OR-A5JI TCGA-OR-A5JL TCGA-OR-A5JQ TCGA-OR-A5JR TCGA-OR-A5JT 
       91.46        46.82        22.03        36.26       121.25        29.82 
TCGA-OR-A5JV TCGA-OR-A5JZ TCGA-OR-A5K1 TCGA-OR-A5K3 TCGA-OR-A5K4 TCGA-OR-A5L4 
       66.51        27.02        96.59       100.18        22.98        31.79 
TCGA-OR-A5L5 TCGA-OR-A5L6 TCGA-OR-A5L9 TCGA-OR-A5LA TCGA-OR-A5LH TCGA-OR-A5LK 
       43.30        28.31        28.64        23.64        78.41        73.05 
TCGA-OR-A5LN TCGA-OR-A5LP TCGA-OR-A5LR TCGA-OR-A5LT TCGA-PA-A5YG TCGA-PK-A5H8 
       62.99        61.05        28.04        18.05        24.85       119.11 
TCGA-PK-A5HA 
       39.48 

subtype1 subtype2 subtype3 subtype4 
    4.11     6.81    12.59    18.05 
subtype1 subtype2 subtype3 subtype4 
  152.15   153.63    95.18   121.25 
subtype1 subtype2 subtype3 subtype4 
  33.830   41.045   20.250   39.480 
[1] "4.1 - 152.2 (33.8)"  "6.8 - 153.6 (41.0)"  "12.6 - 95.2 (20.2)" 
[4] "18.1 - 121.2 (39.5)"
D6V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       2        9         7        5
  subtype2       0        9         5        8
  subtype3       2        2         1        2
  subtype4       5       17         3        0
D6V3, multiclass
           clus
vv          subtype1 subtype2 subtype3 subtype4
  STAGE I          2        0        2        5
  STAGE II         9        9        2       17
  STAGE III        7        5        1        3
  STAGE IV         5        8        2        0
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  2 12  4  5
  subtype2  0 11  2  9
  subtype3  2  2  1  2
  subtype4  5 17  1  2
D6V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  T1        2        0        2        5
  T2       12       11        2       17
  T3        4        2        1        1
  T4        5        9        2        2
[1] 4 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D6V5, binary
          cls
clus        0  1
  subtype1 19  4
  subtype2 17  5
  subtype3  7  0
  subtype4 25  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   19    4
  subtype2   17    5
  subtype3    7    0
  subtype4   25    0
   clus
vv  subtype1 subtype2 subtype3 subtype4
  0       19       17        7       25
  1        4        5        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"
D6V6, binary
          cls
clus        0  1
  subtype1 17  6
  subtype2 13 11
  subtype3  5  2
  subtype4 13 12
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   17    6
  subtype2   13   11
  subtype3    5    2
  subtype4   13   12
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       17       13        5       13
  MALE          6       11        2       12
[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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    22
  subtype2     0                         0    20
  subtype3     1                         1     5
  subtype4     0                         0    19
D6V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            0        0        1        0
  BLACK OR AFRICAN AMERICAN        0        0        1        0
  WHITE                           22       20        5       19
[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"
D6V8, binary
          cls
clus        0  1
  subtype1  2 10
  subtype2  3  9
  subtype3  2  3
  subtype4  0  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   10
  subtype2    3    9
  subtype3    2    3
  subtype4    0    8
                        clus
vv                       subtype1 subtype2 subtype3 subtype4
  HISPANIC OR LATINO            2        3        2        0
  NOT HISPANIC OR LATINO       10        9        3        8
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(7) Variable = MIRSEQ_CNMF
D7V1, survival
          sevent
clus2       0  1
  subtype1 22 16
  subtype2  7  9
  subtype3 23  3
subtype1 subtype2 subtype3 
      38       16       26 
subtype1 subtype2 subtype3 
      16        9        3 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J3 TCGA-OR-A5J4 TCGA-OR-A5J5 TCGA-OR-A5J6 TCGA-OR-A5J7 
       44.55        68.75        13.91        12.00        88.87        16.11 
TCGA-OR-A5JA TCGA-OR-A5JE TCGA-OR-A5JG TCGA-OR-A5JJ TCGA-OR-A5JK TCGA-OR-A5JL 
       30.31        69.21        17.79        16.11        49.22        22.03 
TCGA-OR-A5JP TCGA-OR-A5JS TCGA-OR-A5K2 TCGA-OR-A5K4 TCGA-OR-A5K6 TCGA-OR-A5K9 
       15.25        12.59        32.68        22.98        49.08        11.31 
TCGA-OR-A5KO TCGA-OR-A5KT TCGA-OR-A5KV TCGA-OR-A5KW TCGA-OR-A5KX TCGA-OR-A5KZ 
       46.49        95.18       127.50        50.37        44.84         4.11 
TCGA-OR-A5L4 TCGA-OR-A5L8 TCGA-OR-A5LB TCGA-OR-A5LC TCGA-OR-A5LD TCGA-OR-A5LE 
       31.79        29.10        39.58         5.23        39.35        21.76 
TCGA-OR-A5LG TCGA-OR-A5LM TCGA-OR-A5LO TCGA-OR-A5LS TCGA-OU-A5PI TCGA-P6-A5OF 
       52.24        61.08        69.11        36.03        38.50         6.81 
TCGA-PK-A5H8 TCGA-PK-A5H9 
      119.11        20.25 

$subtype2
TCGA-OR-A5J2 TCGA-OR-A5J8 TCGA-OR-A5J9 TCGA-OR-A5JB TCGA-OR-A5JF TCGA-OR-A5JM 
       55.13        19.04        44.45        18.12        66.25        18.48 
TCGA-OR-A5JY TCGA-OR-A5K0 TCGA-OR-A5K5 TCGA-OR-A5K8 TCGA-OR-A5KU TCGA-OR-A5KY 
       18.15        33.83        16.37        24.62       153.63        12.85 
TCGA-OR-A5L3 TCGA-OR-A5LJ TCGA-P6-A5OG TCGA-PK-A5HB 
      152.15        36.33        12.59        42.51 

$subtype3
TCGA-OR-A5JC TCGA-OR-A5JD TCGA-OR-A5JI TCGA-OR-A5JO TCGA-OR-A5JQ TCGA-OR-A5JR 
       57.53        91.46        46.82        29.23        36.26       121.25 
TCGA-OR-A5JT TCGA-OR-A5JV TCGA-OR-A5JW TCGA-OR-A5JX TCGA-OR-A5JZ TCGA-OR-A5K1 
       29.82        66.51        72.39        31.23        27.02        96.59 
TCGA-OR-A5K3 TCGA-OR-A5L5 TCGA-OR-A5L6 TCGA-OR-A5L9 TCGA-OR-A5LA TCGA-OR-A5LH 
      100.18        43.30        28.31        28.64        23.64        78.41 
TCGA-OR-A5LK TCGA-OR-A5LL TCGA-OR-A5LN TCGA-OR-A5LP TCGA-OR-A5LR TCGA-OR-A5LT 
       73.05        53.03        62.99        61.05        28.04        18.05 
TCGA-PA-A5YG TCGA-PK-A5HA 
       24.85        39.48 

subtype1 subtype2 subtype3 
    4.11    12.59    18.05 
subtype1 subtype2 subtype3 
  127.50   153.63   121.25 
subtype1 subtype2 subtype3 
  34.355   29.225   45.060 
[1] "4.1 - 127.5 (34.4)"  "12.6 - 153.6 (29.2)" "18.1 - 121.2 (45.1)"
D7V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       3       14        12        9
  subtype2       1        5         2        7
  subtype3       5       18         2        0
D7V3, multiclass
           clus
vv          subtype1 subtype2 subtype3
  STAGE I          3        1        5
  STAGE II        14        5       18
  STAGE III       12        2        2
  STAGE IV         9        7        0
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  3 18  4 13
  subtype2  1  6  3  5
  subtype3  5 18  2  0
D7V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T1        3        1        5
  T2       18        6       18
  T3        4        3        2
  T4       13        5        0
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D7V5, binary
          cls
clus        0  1
  subtype1 31  7
  subtype2 12  3
  subtype3 25  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   31    7
  subtype2   12    3
  subtype3   25    0
   clus
vv  subtype1 subtype2 subtype3
  0       31       12       25
  1        7        3        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"
D7V6, binary
          cls
clus        0  1
  subtype1 25 13
  subtype2 12  4
  subtype3 12 14
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   25   13
  subtype2   12    4
  subtype3   12   14
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       25       12       12
  MALE         13        4       14
[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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         1    33
  subtype2     0                         0    15
  subtype3     0                         0    19
D7V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        0        0
  BLACK OR AFRICAN AMERICAN        1        0        0
  WHITE                           33       15       19
[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"
D7V8, binary
          cls
clus        0  1
  subtype1  5 18
  subtype2  3  6
  subtype3  0  6
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5   18
  subtype2    3    6
  subtype3    0    6
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            5        3        0
  NOT HISPANIC OR LATINO       18        6        6
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(8) Variable = MIRSEQ_CHIERARCHICAL
D8V1, survival
          sevent
clus2       0  1
  subtype1  9  8
  subtype2 20  7
  subtype3 12  0
  subtype4  9 11
  subtype5  2  2
subtype1 subtype2 subtype3 subtype4 subtype5 
      17       27       12       20        4 
subtype1 subtype2 subtype3 subtype4 subtype5 
       8        7        0       11        2 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J3 TCGA-OR-A5J4 TCGA-OR-A5J5 TCGA-OR-A5JA TCGA-OR-A5JC 
       44.55        68.75        13.91        12.00        30.31        57.53 
TCGA-OR-A5JJ TCGA-OR-A5JK TCGA-OR-A5JX TCGA-OR-A5K3 TCGA-OR-A5K4 TCGA-OR-A5KW 
       16.11        49.22        31.23       100.18        22.98        50.37 
TCGA-OR-A5KZ TCGA-OR-A5LG TCGA-OR-A5LM TCGA-OR-A5LO TCGA-P6-A5OF 
        4.11        52.24        61.08        69.11         6.81 

$subtype2
TCGA-OR-A5J2 TCGA-OR-A5J9 TCGA-OR-A5JB TCGA-OR-A5JD TCGA-OR-A5JF TCGA-OR-A5JM 
       55.13        44.45        18.12        91.46        66.25        18.48 
TCGA-OR-A5JQ TCGA-OR-A5JR TCGA-OR-A5JT TCGA-OR-A5JV TCGA-OR-A5JW TCGA-OR-A5JY 
       36.26       121.25        29.82        66.51        72.39        18.15 
TCGA-OR-A5JZ TCGA-OR-A5K0 TCGA-OR-A5K1 TCGA-OR-A5K8 TCGA-OR-A5KU TCGA-OR-A5KY 
       27.02        33.83        96.59        24.62       153.63        12.85 
TCGA-OR-A5L6 TCGA-OR-A5L9 TCGA-OR-A5LH TCGA-OR-A5LK TCGA-OR-A5LP TCGA-OR-A5LR 
       28.31        28.64        78.41        73.05        61.05        28.04 
TCGA-P6-A5OG TCGA-PA-A5YG TCGA-PK-A5HA 
       12.59        24.85        39.48 

$subtype3
TCGA-OR-A5J6 TCGA-OR-A5JI TCGA-OR-A5JL TCGA-OR-A5JO TCGA-OR-A5KO TCGA-OR-A5L4 
       88.87        46.82        22.03        29.23        46.49        31.79 
TCGA-OR-A5L5 TCGA-OR-A5LA TCGA-OR-A5LN TCGA-OR-A5LT TCGA-PK-A5H8 TCGA-PK-A5H9 
       43.30        23.64        62.99        18.05       119.11        20.25 

$subtype4
TCGA-OR-A5J7 TCGA-OR-A5J8 TCGA-OR-A5JE TCGA-OR-A5JG TCGA-OR-A5JP TCGA-OR-A5JS 
       16.11        19.04        69.21        17.79        15.25        12.59 
TCGA-OR-A5K2 TCGA-OR-A5K5 TCGA-OR-A5K9 TCGA-OR-A5KT TCGA-OR-A5KV TCGA-OR-A5KX 
       32.68        16.37        11.31        95.18       127.50        44.84 
TCGA-OR-A5L3 TCGA-OR-A5L8 TCGA-OR-A5LC TCGA-OR-A5LD TCGA-OR-A5LE TCGA-OR-A5LJ 
      152.15        29.10         5.23        39.35        21.76        36.33 
TCGA-OR-A5LS TCGA-PK-A5HB 
       36.03        42.51 

$subtype5
TCGA-OR-A5K6 TCGA-OR-A5LB TCGA-OR-A5LL TCGA-OU-A5PI 
       49.08        39.58        53.03        38.50 

subtype1 subtype2 subtype3 subtype4 subtype5 
    4.11    12.59    18.05     5.23    38.50 
subtype1 subtype2 subtype3 subtype4 subtype5 
  100.18   153.63   119.11   152.15    53.03 
subtype1 subtype2 subtype3 subtype4 subtype5 
  44.550   36.260   37.545   30.890   44.330 
[1] "4.1 - 100.2 (44.5)"  "12.6 - 153.6 (36.3)" "18.1 - 119.1 (37.5)"
[4] "5.2 - 152.2 (30.9)"  "38.5 - 53.0 (44.3)" 
D8V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       0        5         7        4
  subtype2       2       19         0        6
  subtype3       4        5         2        1
  subtype4       3        6         7        3
  subtype5       0        2         0        2
D8V3, multiclass
           clus
vv          subtype1 subtype2 subtype3 subtype4 subtype5
  STAGE I          0        2        4        3        0
  STAGE II         5       19        5        6        2
  STAGE III        7        0        2        7        0
  STAGE IV         4        6        1        3        2
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  0  6  4  6
  subtype2  2 19  1  5
  subtype3  4  5  1  2
  subtype4  3  9  3  4
  subtype5  0  3  0  1
D8V4, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5
  T1        0        2        4        3        0
  T2        6       19        5        9        3
  T3        4        1        1        3        0
  T4        6        5        2        4        1
[1] 4 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V5, binary
          cls
clus        0  1
  subtype1 13  3
  subtype2 25  2
  subtype3 12  0
  subtype4 15  4
  subtype5  3  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   13    3
  subtype2   25    2
  subtype3   12    0
  subtype4   15    4
  subtype5    3    1
   clus
vv  subtype1 subtype2 subtype3 subtype4 subtype5
  0       13       25       12       15        3
  1        3        2        0        4        1
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V6, binary
          cls
clus        0  1
  subtype1  7 10
  subtype2 16 11
  subtype3  9  3
  subtype4 14  6
  subtype5  3  1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7   10
  subtype2   16   11
  subtype3    9    3
  subtype4   14    6
  subtype5    3    1
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5
  FEMALE        7       16        9       14        3
  MALE         10       11        3        6        1
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    15
  subtype2     0                         0    23
  subtype3     1                         1     8
  subtype4     0                         0    18
  subtype5     0                         0     3
D8V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            0        0        1        0        0
  BLACK OR AFRICAN AMERICAN        0        0        1        0        0
  WHITE                           15       23        8       18        3
[1] 3 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D8V8, binary
          cls
clus       0 1
  subtype1 3 4
  subtype2 2 8
  subtype3 1 6
  subtype4 2 9
  subtype5 0 3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3    4
  subtype2    2    8
  subtype3    1    6
  subtype4    2    9
  subtype5    0    3
                        clus
vv                       subtype1 subtype2 subtype3 subtype4 subtype5
  HISPANIC OR LATINO            3        2        1        2        0
  NOT HISPANIC OR LATINO        4        8        6        9        3
[1] 2 5
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(9) Variable = MIRSEQ_MATURE_CNMF
D9V1, survival
          sevent
clus2       0  1
  subtype1 19 10
  subtype2  8 14
  subtype3 23  4
subtype1 subtype2 subtype3 
      29       22       27 
subtype1 subtype2 subtype3 
      10       14        4 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J3 TCGA-OR-A5J5 TCGA-OR-A5J6 TCGA-OR-A5JA TCGA-OR-A5JE 
       44.55        68.75        12.00        88.87        30.31        69.21 
TCGA-OR-A5JG TCGA-OR-A5JJ TCGA-OR-A5JK TCGA-OR-A5JL TCGA-OR-A5JP TCGA-OR-A5K4 
       17.79        16.11        49.22        22.03        15.25        22.98 
TCGA-OR-A5K9 TCGA-OR-A5KO TCGA-OR-A5KT TCGA-OR-A5KV TCGA-OR-A5KW TCGA-OR-A5KZ 
       11.31        46.49        95.18       127.50        50.37         4.11 
TCGA-OR-A5L3 TCGA-OR-A5L4 TCGA-OR-A5L8 TCGA-OR-A5LA TCGA-OR-A5LG TCGA-OR-A5LJ 
      152.15        31.79        29.10        23.64        52.24        36.33 
TCGA-OR-A5LO TCGA-OR-A5LS TCGA-OU-A5PI TCGA-P6-A5OF TCGA-PK-A5H9 
       69.11        36.03        38.50         6.81        20.25 

$subtype2
TCGA-OR-A5J2 TCGA-OR-A5J4 TCGA-OR-A5J7 TCGA-OR-A5J9 TCGA-OR-A5JB TCGA-OR-A5JM 
       55.13        13.91        16.11        44.45        18.12        18.48 
TCGA-OR-A5JS TCGA-OR-A5JY TCGA-OR-A5K0 TCGA-OR-A5K2 TCGA-OR-A5K5 TCGA-OR-A5K6 
       12.59        18.15        33.83        32.68        16.37        49.08 
TCGA-OR-A5K8 TCGA-OR-A5KU TCGA-OR-A5KX TCGA-OR-A5KY TCGA-OR-A5LB TCGA-OR-A5LC 
       24.62       153.63        44.84        12.85        39.58         5.23 
TCGA-OR-A5LD TCGA-OR-A5LE TCGA-P6-A5OG TCGA-PK-A5HB 
       39.35        21.76        12.59        42.51 

$subtype3
TCGA-OR-A5J8 TCGA-OR-A5JC TCGA-OR-A5JD TCGA-OR-A5JF TCGA-OR-A5JI TCGA-OR-A5JO 
       19.04        57.53        91.46        66.25        46.82        29.23 
TCGA-OR-A5JQ TCGA-OR-A5JR TCGA-OR-A5JT TCGA-OR-A5JV TCGA-OR-A5JW TCGA-OR-A5JX 
       36.26       121.25        29.82        66.51        72.39        31.23 
TCGA-OR-A5JZ TCGA-OR-A5K1 TCGA-OR-A5K3 TCGA-OR-A5L5 TCGA-OR-A5L6 TCGA-OR-A5L9 
       27.02        96.59       100.18        43.30        28.31        28.64 
TCGA-OR-A5LH TCGA-OR-A5LK TCGA-OR-A5LL TCGA-OR-A5LN TCGA-OR-A5LP TCGA-OR-A5LR 
       78.41        73.05        53.03        62.99        61.05        28.04 
TCGA-OR-A5LT TCGA-PA-A5YG TCGA-PK-A5HA 
       18.05        24.85        39.48 

subtype1 subtype2 subtype3 
    4.11     5.23    18.05 
subtype1 subtype2 subtype3 
  152.15   153.63   121.25 
subtype1 subtype2 subtype3 
   36.03    23.19    46.82 
[1] "4.1 - 152.2 (36.0)"  "5.2 - 153.6 (23.2)"  "18.1 - 121.2 (46.8)"
D9V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       4       10         8        7
  subtype2       0        7         5        9
  subtype3       5       18         3        0
D9V3, multiclass
           clus
vv          subtype1 subtype2 subtype3
  STAGE I          4        0        5
  STAGE II        10        7       18
  STAGE III        8        5        3
  STAGE IV         7        9        0
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  4 14  2  9
  subtype2  0  8  4  9
  subtype3  5 18  3  0
D9V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T1        4        0        5
  T2       14        8       18
  T3        2        4        3
  T4        9        9        0
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V5, binary
          cls
clus        0  1
  subtype1 23  6
  subtype2 17  4
  subtype3 26  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   23    6
  subtype2   17    4
  subtype3   26    0
   clus
vv  subtype1 subtype2 subtype3
  0       23       17       26
  1        6        4        0
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D9V6, binary
          cls
clus        0  1
  subtype1 21  8
  subtype2 16  6
  subtype3 12 15
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   21    8
  subtype2   16    6
  subtype3   12   15
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       21       16       12
  MALE          8        6       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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         1    25
  subtype2     0                         0    21
  subtype3     0                         0    20
D9V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        0        0
  BLACK OR AFRICAN AMERICAN        1        0        0
  WHITE                           25       21       20
[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"
D9V8, binary
          cls
clus        0  1
  subtype1  3 14
  subtype2  4 10
  subtype3  1  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3   14
  subtype2    4   10
  subtype3    1    5
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            3        4        1
  NOT HISPANIC OR LATINO       14       10        5
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(10) Variable = MIRSEQ_MATURE_CHIERARCHICAL
D10V1, survival
          sevent
clus2       0  1
  subtype1 21 19
  subtype2 19  5
  subtype3 10  4
subtype1 subtype2 subtype3 
      40       24       14 
subtype1 subtype2 subtype3 
      19        5        4 
$subtype1
TCGA-OR-A5J1 TCGA-OR-A5J3 TCGA-OR-A5J4 TCGA-OR-A5J5 TCGA-OR-A5J6 TCGA-OR-A5J7 
       44.55        68.75        13.91        12.00        88.87        16.11 
TCGA-OR-A5JA TCGA-OR-A5JE TCGA-OR-A5JG TCGA-OR-A5JJ TCGA-OR-A5JK TCGA-OR-A5JL 
       30.31        69.21        17.79        16.11        49.22        22.03 
TCGA-OR-A5JP TCGA-OR-A5JS TCGA-OR-A5K2 TCGA-OR-A5K4 TCGA-OR-A5K5 TCGA-OR-A5K6 
       15.25        12.59        32.68        22.98        16.37        49.08 
TCGA-OR-A5K9 TCGA-OR-A5KO TCGA-OR-A5KT TCGA-OR-A5KV TCGA-OR-A5KW TCGA-OR-A5KX 
       11.31        46.49        95.18       127.50        50.37        44.84 
TCGA-OR-A5KZ TCGA-OR-A5L3 TCGA-OR-A5L4 TCGA-OR-A5L8 TCGA-OR-A5LB TCGA-OR-A5LC 
        4.11       152.15        31.79        29.10        39.58         5.23 
TCGA-OR-A5LD TCGA-OR-A5LE TCGA-OR-A5LG TCGA-OR-A5LJ TCGA-OR-A5LL TCGA-OR-A5LO 
       39.35        21.76        52.24        36.33        53.03        69.11 
TCGA-OR-A5LS TCGA-OU-A5PI TCGA-P6-A5OF TCGA-PK-A5HB 
       36.03        38.50         6.81        42.51 

$subtype2
TCGA-OR-A5J2 TCGA-OR-A5J9 TCGA-OR-A5JF TCGA-OR-A5JM TCGA-OR-A5JQ TCGA-OR-A5JR 
       55.13        44.45        66.25        18.48        36.26       121.25 
TCGA-OR-A5JT TCGA-OR-A5JV TCGA-OR-A5JW TCGA-OR-A5JY TCGA-OR-A5JZ TCGA-OR-A5K0 
       29.82        66.51        72.39        18.15        27.02        33.83 
TCGA-OR-A5K1 TCGA-OR-A5K8 TCGA-OR-A5KU TCGA-OR-A5KY TCGA-OR-A5L6 TCGA-OR-A5L9 
       96.59        24.62       153.63        12.85        28.31        28.64 
TCGA-OR-A5LH TCGA-OR-A5LK TCGA-OR-A5LP TCGA-OR-A5LR TCGA-PA-A5YG TCGA-PK-A5HA 
       78.41        73.05        61.05        28.04        24.85        39.48 

$subtype3
TCGA-OR-A5J8 TCGA-OR-A5JB TCGA-OR-A5JC TCGA-OR-A5JD TCGA-OR-A5JI TCGA-OR-A5JO 
       19.04        18.12        57.53        91.46        46.82        29.23 
TCGA-OR-A5JX TCGA-OR-A5K3 TCGA-OR-A5L5 TCGA-OR-A5LA TCGA-OR-A5LN TCGA-OR-A5LT 
       31.23       100.18        43.30        23.64        62.99        18.05 
TCGA-P6-A5OG TCGA-PK-A5H9 
       12.59        20.25 

subtype1 subtype2 subtype3 
    4.11    12.85    12.59 
subtype1 subtype2 subtype3 
  152.15   153.63   100.18 
subtype1 subtype2 subtype3 
   36.18    37.87    30.23 
[1] "4.1 - 152.2 (36.2)"  "12.8 - 153.6 (37.9)" "12.6 - 100.2 (30.2)"
D10V2, continuous
          vv
clus       STAGE I STAGE II STAGE III STAGE IV
  subtype1       4       12        13       10
  subtype2       2       18         0        4
  subtype3       3        5         3        2
D10V3, multiclass
           clus
vv          subtype1 subtype2 subtype3
  STAGE I          4        2        3
  STAGE II        12       18        5
  STAGE III       13        0        3
  STAGE IV        10        4        2
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       T1 T2 T3 T4
  subtype1  4 17  5 13
  subtype2  2 18  1  3
  subtype3  3  5  3  2
D10V4, multiclass
    clus
vv   subtype1 subtype2 subtype3
  T1        4        2        3
  T2       17       18        5
  T3        5        1        3
  T4       13        3        2
[1] 4 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D10V5, binary
          cls
clus        0  1
  subtype1 31  8
  subtype2 22  2
  subtype3 13  0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   31    8
  subtype2   22    2
  subtype3   13    0
   clus
vv  subtype1 subtype2 subtype3
  0       31       22       13
  1        8        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"
D10V6, binary
          cls
clus        0  1
  subtype1 28 12
  subtype2 14 10
  subtype3  7  7
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   28   12
  subtype2   14   10
  subtype3    7    7
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       28       14        7
  MALE         12       10        7
[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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         1    35
  subtype2     0                         0    20
  subtype3     1                         0    11
D10V7, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            0        0        1
  BLACK OR AFRICAN AMERICAN        1        0        0
  WHITE                           35       20       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"
D10V8, binary
          cls
clus        0  1
  subtype1  5 18
  subtype2  2  7
  subtype3  1  4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5   18
  subtype2    2    7
  subtype3    1    4
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            5        2        1
  NOT HISPANIC OR LATINO       18        7        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"
