[1] "terrence_modification_tag"
[1] TRUE
[1] "nver"         "-nVNozzle.R1"
[1] "nfn"                                 "/xchip/tcga/Tools/Nozzle/v1.current"
[1] "Nozzle.R1"
[1] "successfully load Nozzle.R1"
[1] "ofn"        "-oTTGCT-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/TGCT-TP/11541779/TGCT-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/TGCT-TP/11589202/TGCT-TP.mergedcluster.txt"

nPatients in clinical file=31, in cluster file=150, common to both=31
[1]  8 31
[1] "CN_CNMF"
[1] 3
 1  2  3 
 7  7 17 
 1  2  3 
 7  7 17 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3 
 6 14 11 
 1  2  3 
 6 14 11 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2  3 
10 11 10 
 1  2  3 
10 11 10 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
1 2 3 4 5 6 7 
6 4 2 5 2 8 4 
1 2 4 6 7 
6 4 5 8 4 
[1] "MIRSEQ_CNMF"
[1] 3
1 2 3 4 
2 4 4 3 
2 3 4 
4 4 3 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
1 2 3 
5 4 4 
1 2 3 
5 4 4 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
1 2 3 4 
2 3 3 5 
2 3 4 
3 3 5 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
1 2 3 4 5 6 7 
1 1 4 3 1 1 2 
3 4 
4 3 
[1] "terrence_modification_tag"
[1] TRUE
[1] "data2feature, selection=ALL"
 [1] "YEARSTOBIRTH"                          
 [2] "VITALSTATUS"                           
 [3] "DAYSTODEATH"                           
 [4] "DAYSTOLASTFOLLOWUP"                    
 [5] "NEOPLASM.DISEASESTAGE"                 
 [6] "PATHOLOGY.T.STAGE"                     
 [7] "PATHOLOGY.N.STAGE"                     
 [8] "PATHOLOGY.M.STAGE"                     
 [9] "DCCUPLOADDATE"                         
[10] "GENDER"                                
[11] "RADIATIONTHERAPY"                      
[12] "RADIATIONS.RADIATION.REGIMENINDICATION"
[13] "RACE"                                  
[14] "ETHNICITY"                             
[15] "BATCHNUMBER"                           

Input Data has 15 rows and 31 columns.

[1] "Batch" "15"   
[1] "Last Follow UP"
TCGA-2G-AAF6 TCGA-2G-AAFL TCGA-2G-AAFZ TCGA-2G-AAG9 TCGA-2G-AAGE TCGA-2G-AAGG 
        3113          428         1122         1926         2080         2067 
TCGA-2G-AAGI TCGA-2G-AAGJ TCGA-2G-AAGM TCGA-2G-AAGN TCGA-2G-AAGO TCGA-2G-AAGP 
        2801         2284         1814         3236         3498         3669 
TCGA-2G-AAGV TCGA-2G-AAGW TCGA-2G-AAGY TCGA-2G-AAH4 TCGA-2G-AAHC TCGA-2G-AAHG 
        3922         1869         2462         3823         1817         1819 
TCGA-2G-AAKD TCGA-2G-AAKM TCGA-2G-AAL7 TCGA-2X-A9D6 TCGA-SO-A8JP TCGA-X3-A8G4 
        3726         2651         3991            4          107          856 
TCGA-XE-A8H1 TCGA-XE-AANR TCGA-XE-AAOJ TCGA-XE-AAOL TCGA-XY-A8S3 TCGA-ZM-AA05 
         209           14         1550           13          424          757 
TCGA-ZM-AA06 
        1197 
Variable 1:'AGE':	nDistinctValues=19,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 2:'VITALSTATUS':	nDistinctValues=2,	numeric=TRUE,	binary=TRUE,	exclude=TRUE.
Variable 3:'DAYSTODEATH':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 4:'DAYSTOLASTFOLLOWUP':	nDistinctValues=31,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
Variable 5:'NEOPLASM.DISEASESTAGE':	nDistinctValues=10,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 6:'PATHOLOGY.T.STAGE':	nDistinctValues=3,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 7:'PATHOLOGY.N.STAGE':	nDistinctValues=3,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 8:'PATHOLOGY.M.STAGE':	nDistinctValues=3,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 9:'DCCUPLOADDAY':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 10:'GENDER':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 11:'RADIATION.THERAPY':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 12:'RADIATIONS.RADIATION.REGIMENINDICATION':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 13:'RACE':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 14:'ETHNICITY':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 15:'BATCH.NUMBER':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "rownames(nsurv.mat)"
[1] "AGE"                   "NEOPLASM.DISEASESTAGE" "PATHOLOGY.T.STAGE"    
[4] "PATHOLOGY.N.STAGE"     "ETHNICITY"            
[1] "TUMOR.?STAGE"
[1] "TUMOR.?GRADE"
[1] "PATHOLOGY.T" "3"          
[1] "PATHOLOGY.N" "4"          
Output Data has 31 columns, 0 survival variables, and 5 non-survival variables.
AGE, nv=19, binary=FALSE, numeric=TRUE
NEOPLASM.DISEASESTAGE, nv=10, binary=FALSE, numeric=FALSE
PATHOLOGY.T.STAGE, nv=3, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.T',vnm)"
vv
T1 T2 T3 
15 14  2 
[1] "table(vv)"
vv
   T1 T2+T3 
   15    16 
$ClinVariableName
[1] "PATHOLOGY.T.STAGE"

$Table
vv
T1 T2 T3 
15 14  2 

$ClinVariableType
[1] "binary"

$Class0_nSamples
[1] 15

$Class1_nSamples
[1] 16

$Class0_label
[1] "T1"

$Class1_label
[1] "T2+T3"


   T1 T2+T3 
   15    16 
PATHOLOGY.N.STAGE, nv=2, binary=FALSE, numeric=TRUE
ETHNICITY, nv=2, binary=FALSE, numeric=FALSE

Clustering(1) Variable = CN_CNMF
D1V1, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIC STAGE III
  subtype1       1        1        1        0         1         1         0
  subtype2       3        0        0        0         0         0         1
  subtype3       1        0        1        3         0         0         1
          vv
clus       STAGE IIIB STAGE IIIC STAGE IS
  subtype1          0          0        2
  subtype2          0          0        3
  subtype3          2          1        8
D1V2, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           1        3        1
  STAGE IA          1        0        0
  STAGE IB          1        0        1
  STAGE II          0        0        3
  STAGE IIA         1        0        0
  STAGE IIC         1        0        0
  STAGE III         0        1        1
  STAGE IIIB        0        0        2
  STAGE IIIC        0        0        1
  STAGE IS          2        3        8
[1] 10  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
  subtype1  3     4
  subtype2  4     3
  subtype3  8     9
D1V3, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T1           3        4        8
  T2+T3        4        3        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"
D1V4, binary
          cls
clus       0 1
  subtype1 2 1
  subtype2 4 0
  subtype3 7 3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2    1
  subtype2    4    0
  subtype3    7    3
   clus
vv  subtype1 subtype2 subtype3
  0        2        4        7
  1        1        0        3
[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"
D1V5, binary
          cls
clus        0  1
  subtype1  1  6
  subtype2  1  6
  subtype3  1 16
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    1    6
  subtype2    1    6
  subtype3    1   16
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            1        1        1
  NOT HISPANIC OR LATINO        6        6       16
[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, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIC STAGE III
  subtype1       1        0        1        0         0         1         0
  subtype2       1        1        1        1         1         0         1
  subtype3       3        0        0        2         0         0         1
          vv
clus       STAGE IIIB STAGE IIIC STAGE IS
  subtype1          1          0        2
  subtype2          1          0        7
  subtype3          0          1        4
D2V2, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           1        1        3
  STAGE IA          0        1        0
  STAGE IB          1        1        0
  STAGE II          0        1        2
  STAGE IIA         0        1        0
  STAGE IIC         1        0        0
  STAGE III         0        1        1
  STAGE IIIB        1        1        0
  STAGE IIIC        0        0        1
  STAGE IS          2        7        4
[1] 10  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
  subtype1  3     3
  subtype2  4    10
  subtype3  8     3
D2V3, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T1           3        4        8
  T2+T3        3       10        3
[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"
D2V4, binary
          cls
clus       0 1
  subtype1 1 1
  subtype2 7 2
  subtype3 5 1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    1    1
  subtype2    7    2
  subtype3    5    1
   clus
vv  subtype1 subtype2 subtype3
  0        1        7        5
  1        1        2        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"
D2V5, binary
          cls
clus        0  1
  subtype1  0  6
  subtype2  2 12
  subtype3  1 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    0    6
  subtype2    2   12
  subtype3    1   10
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            0        2        1
  NOT HISPANIC OR LATINO        6       12       10
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(3) Variable = MRNASEQ_CNMF
D3V1, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIC STAGE III
  subtype1       5        0        1        0         0         1         0
  subtype2       0        1        1        1         0         0         1
  subtype3       0        0        0        2         1         0         1
          vv
clus       STAGE IIIB STAGE IIIC STAGE IS
  subtype1          1          0        2
  subtype2          1          0        6
  subtype3          0          1        5
D3V2, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           5        0        0
  STAGE IA          0        1        0
  STAGE IB          1        1        0
  STAGE II          0        1        2
  STAGE IIA         0        0        1
  STAGE IIC         1        0        0
  STAGE III         0        1        1
  STAGE IIIB        1        1        0
  STAGE IIIC        0        0        1
  STAGE IS          2        6        5
[1] 10  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
  subtype1  6     4
  subtype2  3     8
  subtype3  6     4
D3V3, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T1           6        3        6
  T2+T3        4        8        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"
D3V4, binary
          cls
clus       0 1
  subtype1 3 1
  subtype2 6 1
  subtype3 4 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    3    1
  subtype2    6    1
  subtype3    4    2
   clus
vv  subtype1 subtype2 subtype3
  0        3        6        4
  1        1        1        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"
D3V5, binary
          cls
clus        0  1
  subtype1  1  9
  subtype2  1 10
  subtype3  1  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    1    9
  subtype2    1   10
  subtype3    1    9
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            1        1        1
  NOT HISPANIC OR LATINO        9       10        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(4) Variable = MRNASEQ_CHIERARCHICAL
D4V1, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIC STAGE III
  subtype1       2        0        1        0         0         1         0
  subtype2       3        0        0        0         0         0         0
  subtype4       0        0        0        1         1         0         0
  subtype6       0        1        0        1         0         0         1
  subtype7       0        0        0        1         0         0         1
          vv
clus       STAGE IIIB STAGE IIIC STAGE IS
  subtype1          1          0        1
  subtype2          0          0        1
  subtype4          0          1        2
  subtype6          1          0        4
  subtype7          0          0        2
D4V2, multiclass
            clus
vv           subtype1 subtype2 subtype4 subtype6 subtype7
  STAGE I           2        3        0        0        0
  STAGE IA          0        0        0        1        0
  STAGE IB          1        0        0        0        0
  STAGE II          0        0        1        1        1
  STAGE IIA         0        0        1        0        0
  STAGE IIC         1        0        0        0        0
  STAGE III         0        0        0        1        1
  STAGE IIIB        1        0        0        1        0
  STAGE IIIC        0        0        1        0        0
  STAGE IS          1        1        2        4        2
[1] 10  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
  subtype1  2     4
  subtype2  4     0
  subtype4  3     2
  subtype6  3     5
  subtype7  2     2
D4V3, multiclass
       clus
vv      subtype1 subtype2 subtype4 subtype6 subtype7
  T1           2        4        3        3        2
  T2+T3        4        0        2        5        2
[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"
D4V4, binary
          cls
clus       0 1
  subtype1 0 1
  subtype2 3 0
  subtype4 2 2
  subtype6 5 1
  subtype7 1 0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    0    1
  subtype2    3    0
  subtype4    2    2
  subtype6    5    1
  subtype7    1    0
   clus
vv  subtype1 subtype2 subtype4 subtype6 subtype7
  0        0        3        2        5        1
  1        1        0        2        1        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"
D4V5, binary
          cls
clus       0 1
  subtype1 1 5
  subtype2 0 4
  subtype4 0 5
  subtype6 0 8
  subtype7 1 3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    1    5
  subtype2    0    4
  subtype4    0    5
  subtype6    0    8
  subtype7    1    3
                        clus
vv                       subtype1 subtype2 subtype4 subtype6 subtype7
  HISPANIC OR LATINO            1        0        0        0        1
  NOT HISPANIC OR LATINO        5        4        5        8        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(5) Variable = MIRSEQ_CNMF
D5V1, continuous
          vv
clus       STAGE I STAGE IB STAGE IIA STAGE IIC STAGE IIIC STAGE IS
  subtype2       0        0         0         0          0        4
  subtype3       0        0         1         0          1        2
  subtype4       1        1         0         1          0        0
D5V2, multiclass
            clus
vv           subtype2 subtype3 subtype4
  STAGE I           0        0        1
  STAGE IB          0        0        1
  STAGE IIA         0        1        0
  STAGE IIC         0        0        1
  STAGE IIIC        0        1        0
  STAGE IS          4        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       T1 T2+T3
  subtype2  1     3
  subtype3  2     2
  subtype4  1     2
D5V3, multiclass
       clus
vv      subtype2 subtype3 subtype4
  T1           1        2        1
  T2+T3        3        2        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"
D5V4, binary
          cls
clus       0 1
  subtype2 3 0
  subtype3 1 2
  subtype4 1 0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype2    3    0
  subtype3    1    2
  subtype4    1    0
   clus
vv  subtype2 subtype3 subtype4
  0        3        1        1
  1        0        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"
D5V5, binary
          cls
clus       0 1
  subtype2 0 4
  subtype3 1 3
  subtype4 0 3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype2    0    4
  subtype3    1    3
  subtype4    0    3
                        clus
vv                       subtype2 subtype3 subtype4
  HISPANIC OR LATINO            0        1        0
  NOT HISPANIC OR LATINO        4        3        3
[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, continuous
          vv
clus       STAGE I STAGE IB STAGE IIA STAGE IIC STAGE IIIC STAGE IS
  subtype1       2        1         0         1          0        1
  subtype2       0        0         0         0          0        4
  subtype3       0        0         1         0          1        2
D6V2, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           2        0        0
  STAGE IB          1        0        0
  STAGE IIA         0        0        1
  STAGE IIC         1        0        0
  STAGE IIIC        0        0        1
  STAGE IS          1        4        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       T1 T2+T3
  subtype1  2     3
  subtype2  1     3
  subtype3  2     2
D6V3, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T1           2        1        2
  T2+T3        3        3        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"
D6V4, binary
          cls
clus       0 1
  subtype1 1 0
  subtype2 3 0
  subtype3 1 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    1    0
  subtype2    3    0
  subtype3    1    2
   clus
vv  subtype1 subtype2 subtype3
  0        1        3        1
  1        0        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"
D6V5, binary
          cls
clus       0 1
  subtype1 1 4
  subtype2 0 4
  subtype3 1 3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    1    4
  subtype2    0    4
  subtype3    1    3
                        clus
vv                       subtype1 subtype2 subtype3
  HISPANIC OR LATINO            1        0        1
  NOT HISPANIC OR LATINO        4        4        3
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(7) Variable = MIRSEQ_MATURE_CNMF
D7V1, continuous
          vv
clus       STAGE I STAGE IIA STAGE IIC STAGE IIIC STAGE IS
  subtype2       0         0         0          0        3
  subtype3       1         0         1          0        1
  subtype4       0         1         0          1        3
D7V2, multiclass
            clus
vv           subtype2 subtype3 subtype4
  STAGE I           0        1        0
  STAGE IIA         0        0        1
  STAGE IIC         0        1        0
  STAGE IIIC        0        0        1
  STAGE IS          3        1        3
[1] 5 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
  subtype2  0     3
  subtype3  1     2
  subtype4  3     2
D7V3, multiclass
       clus
vv      subtype2 subtype3 subtype4
  T1           0        1        3
  T2+T3        3        2        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"
D7V4, binary
          cls
clus       0 1
  subtype2 2 0
  subtype3 0 0
  subtype4 2 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype2    2    0
  subtype3    0    0
  subtype4    2    2
   clus
vv  subtype2 subtype4
  0        2        2
  1        0        2
[1] 2 2
[1] FALSE
D7V5, binary
          cls
clus       0 1
  subtype2 0 3
  subtype3 1 2
  subtype4 1 4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype2    0    3
  subtype3    1    2
  subtype4    1    4
                        clus
vv                       subtype2 subtype3 subtype4
  HISPANIC OR LATINO            0        1        1
  NOT HISPANIC OR LATINO        3        2        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, continuous
          vv
clus       STAGE IIA STAGE IIIC STAGE IS
  subtype3         0          0        4
  subtype4         1          1        1
D8V2, multiclass
            clus
vv           subtype3 subtype4
  STAGE IIA         0        1
  STAGE IIIC        0        1
  STAGE IS          4        1
[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"
          vv
clus       T1 T2+T3
  subtype3  1     3
  subtype4  1     2
D8V3, multiclass
       clus
vv      subtype3 subtype4
  T1           1        1
  T2+T3        3        2
[1] 2 2
[1] FALSE
D8V4, binary
          cls
clus       0 1
  subtype3 3 0
  subtype4 0 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype3    3    0
  subtype4    0    2
   clus
vv  subtype3 subtype4
  0        3        0
  1        0        2
[1] 2 2
[1] FALSE
D8V5, binary
          cls
clus       0 1
  subtype3 0 4
  subtype4 1 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype3    0    4
  subtype4    1    2
                        clus
vv                       subtype3 subtype4
  HISPANIC OR LATINO            0        1
  NOT HISPANIC OR LATINO        4        2
[1] 2 2
[1] FALSE
