[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"        "-oTDLBC-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/DLBC-TP/10005821/DLBC-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/DLBC-TP/10668122/DLBC-TP.mergedcluster.txt"

nPatients in clinical file=33, in cluster file=48, common to both=33
[1]  7 33
[1] "METHLYATION_CNMF"
[1] 3
 1  2 
16 17 
 1  2 
16 17 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2 
13 12 
 1  2 
13 12 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
 1  2  3 
12  9  4 
 1  2  3 
12  9  4 
[1] "MIRSEQ_CNMF"
[1] 3
 1  2 
11 13 
 1  2 
11 13 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
1 2 3 4 5 6 7 8 
2 2 3 4 5 2 3 3 
3 4 5 7 8 
3 4 5 3 3 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
1 2 3 
6 9 9 
1 2 3 
6 9 9 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
1 2 3 4 5 6 7 8 9 
2 3 3 2 3 2 4 3 2 
2 3 5 7 8 
3 3 3 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] "DATEOFINITIALPATHOLOGICDIAGNOSIS"      
[12] "RADIATIONTHERAPY"                      
[13] "HISTOLOGICALTYPE"                      
[14] "RADIATIONS.RADIATION.REGIMENINDICATION"
[15] "RACE"                                  
[16] "ETHNICITY"                             
[17] "BATCHNUMBER"                           

Input Data has 17 rows and 33 columns.

[1] "Batch" "17"   
[1] "Last Follow UP"
TCGA-FA-8693 TCGA-FA-A4BB TCGA-FA-A4XK TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FA-A7DS 
         132          132          456            6            6           11 
TCGA-FA-A7Q1 TCGA-FA-A82F TCGA-FA-A86F TCGA-FF-8041 TCGA-FF-8042 TCGA-FF-8043 
          22           25           NA         1081          946          965 
TCGA-FF-8047 TCGA-FF-8061 TCGA-FF-8062 TCGA-FF-A7CQ TCGA-FF-A7CR TCGA-FF-A7CW 
         126          832          679          298           NA          791 
TCGA-FF-A7CX TCGA-FM-8000 TCGA-G8-6324 TCGA-G8-6325 TCGA-G8-6326 TCGA-G8-6906 
         385          139           NA         1581         1441           NA 
TCGA-G8-6907 TCGA-G8-6909 TCGA-G8-6914 TCGA-GR-7351 TCGA-GR-7353 TCGA-GR-A4D4 
          NA         3227         5980         3872         2254          812 
TCGA-GR-A4D5 TCGA-GR-A4D6 TCGA-GR-A4D9 
         751          911         1408 
Variable 1:'AGE':	nDistinctValues=24,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 2:'VITALSTATUS':	nDistinctValues=2,	numeric=TRUE,	binary=TRUE,	exclude=FALSE.
Variable 3:'DAYSTODEATH':	nDistinctValues=5,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
Variable 4:'DAYSTOLASTFOLLOWUP':	nDistinctValues=27,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
Variable 5:'NEOPLASM.DISEASESTAGE':	nDistinctValues=0,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 6:'PATHOLOGY.T.STAGE':	nDistinctValues=0,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 7:'PATHOLOGY.N.STAGE':	nDistinctValues=0,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 8:'PATHOLOGY.M.STAGE':	nDistinctValues=0,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 9:'DCCUPLOADDAY':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 10:'GENDER':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 11:'DAYOFINITIALPATHOLOGICDIAGNOSIS':	nDistinctValues=13,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
Variable 12:'RADIATION.THERAPY':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 13:'HISTOLOGICAL.TYPE':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 14:'RADIATIONS.RADIATION.REGIMENINDICATION':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 15:'RACE':	nDistinctValues=3,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 16:'ETHNICITY':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 17:'BATCH.NUMBER':	nDistinctValues=4,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "rownames(nsurv.mat)"
[1] "AGE"    "GENDER" "RACE"  
[1] "TUMOR.?STAGE"
[1] "TUMOR.?GRADE"
[1] "PATHOLOGY.T"
[1] "PATHOLOGY.N"
Output Data has 33 columns, 1 survival variables, and 3 non-survival variables.
AGE, nv=24, binary=FALSE, numeric=TRUE
GENDER, nv=2, binary=FALSE, numeric=FALSE
RACE, nv=3, binary=FALSE, numeric=FALSE

Clustering(1) Variable = METHLYATION_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 14  1
  subtype2 13  4
subtype1 subtype2 
      15       17 
subtype1 subtype2 
       1        4 
$subtype1
TCGA-FA-8693 TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8062 TCGA-FF-A7CW 
        4.34         4.34         0.20         0.20        22.32        26.01 
TCGA-G8-6324 TCGA-G8-6325 TCGA-G8-6326 TCGA-G8-6914 TCGA-GR-7351 TCGA-GR-7353 
       41.16        51.98        47.38       196.60       127.30        74.10 
TCGA-GR-A4D4 TCGA-GR-A4D5 TCGA-GR-A4D6 
       26.70        24.69        29.95 

$subtype2
TCGA-FA-A4XK TCGA-FA-A7DS TCGA-FA-A7Q1 TCGA-FA-A82F TCGA-FF-8041 TCGA-FF-8042 
       14.99         0.36         0.72         0.82        35.54        31.10 
TCGA-FF-8043 TCGA-FF-8047 TCGA-FF-8061 TCGA-FF-A7CQ TCGA-FF-A7CR TCGA-FF-A7CX 
       31.73         4.14        27.35         9.80        10.29        12.66 
TCGA-FM-8000 TCGA-G8-6906 TCGA-G8-6907 TCGA-G8-6909 TCGA-GR-A4D9 
        4.57       211.23        19.56       106.09        46.29 

subtype1 subtype2 
    0.20     0.36 
subtype1 subtype2 
  196.60   211.23 
subtype1 subtype2 
   26.70    14.99 
[1] "0.2 - 196.6 (26.7)" "0.4 - 211.2 (15.0)"
[1] "hr=" "3.9"
D1V2, continuous
D1V3, binary
          cls
clus        0  1
  subtype1  8  8
  subtype2 10  7
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    8    8
  subtype2   10    7
        clus
vv       subtype1 subtype2
  FEMALE        8       10
  MALE          8        7
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     5                         1    10
  subtype2    12                         0     5
D1V4, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            5       12
  BLACK OR AFRICAN AMERICAN        1        0
  WHITE                           10        5
[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"

Clustering(2) Variable = MRNASEQ_CNMF
D2V1, survival
          sevent
clus2       0  1
  subtype1 11  2
  subtype2 10  2
subtype1 subtype2 
      13       12 
subtype1 subtype2 
       2        2 
$subtype1
TCGA-FA-8693 TCGA-FA-A4XK TCGA-FF-8042 TCGA-FF-8043 TCGA-FF-8061 TCGA-G8-6325 
        4.34        14.99        31.10        31.73        27.35        51.98 
TCGA-G8-6326 TCGA-G8-6906 TCGA-G8-6909 TCGA-G8-6914 TCGA-GR-7351 TCGA-GR-A4D4 
       47.38       211.23       106.09       196.60       127.30        26.70 
TCGA-GR-A4D9 
       46.29 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8041 TCGA-FF-8047 TCGA-FF-8062 
        4.34         0.20         0.20        35.54         4.14        22.32 
TCGA-FM-8000 TCGA-G8-6324 TCGA-G8-6907 TCGA-GR-7353 TCGA-GR-A4D5 TCGA-GR-A4D6 
        4.57        41.16        19.56        74.10        24.69        29.95 

subtype1 subtype2 
    4.34     0.20 
subtype1 subtype2 
  211.23    74.10 
subtype1 subtype2 
   46.29    20.94 
[1] "4.3 - 211.2 (46.3)" "0.2 - 74.1 (20.9)" 
[1] "hr="     "2.2e+09"
D2V2, continuous
D2V3, binary
          cls
clus       0 1
  subtype1 5 8
  subtype2 9 3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5    8
  subtype2    9    3
        clus
vv       subtype1 subtype2
  FEMALE        5        9
  MALE          8        3
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     4                         0     9
  subtype2     6                         1     5
D2V4, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            4        6
  BLACK OR AFRICAN AMERICAN        0        1
  WHITE                            9        5
[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"

Clustering(3) Variable = MRNASEQ_CHIERARCHICAL
D3V1, survival
          sevent
clus2       0  1
  subtype1 10  2
  subtype2  7  2
  subtype3  4  0
subtype1 subtype2 subtype3 
      12        9        4 
subtype1 subtype2 subtype3 
       2        2        0 
$subtype1
TCGA-FA-8693 TCGA-FF-8041 TCGA-FF-8042 TCGA-FF-8043 TCGA-FF-8061 TCGA-FF-8062 
        4.34        35.54        31.10        31.73        27.35        22.32 
TCGA-G8-6325 TCGA-G8-6326 TCGA-G8-6906 TCGA-G8-6909 TCGA-G8-6914 TCGA-GR-7351 
       51.98        47.38       211.23       106.09       196.60       127.30 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8047 TCGA-FM-8000 TCGA-G8-6324 
        4.34         0.20         0.20         4.14         4.57        41.16 
TCGA-G8-6907 TCGA-GR-7353 TCGA-GR-A4D6 
       19.56        74.10        29.95 

$subtype3
TCGA-FA-A4XK TCGA-GR-A4D4 TCGA-GR-A4D5 TCGA-GR-A4D9 
       14.99        26.70        24.69        46.29 

subtype1 subtype2 subtype3 
    4.34     0.20    14.99 
subtype1 subtype2 subtype3 
  211.23    74.10    46.29 
subtype1 subtype2 subtype3 
  41.460    4.570   25.695 
[1] "4.3 - 211.2 (41.5)" "0.2 - 74.1 (4.6)"   "15.0 - 46.3 (25.7)"
D3V2, continuous
D3V3, binary
          cls
clus       0 1
  subtype1 5 7
  subtype2 6 3
  subtype3 3 1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5    7
  subtype2    6    3
  subtype3    3    1
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        5        6        3
  MALE          7        3        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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     5                         0     7
  subtype2     4                         1     4
  subtype3     1                         0     3
D3V4, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            5        4        1
  BLACK OR AFRICAN AMERICAN        0        1        0
  WHITE                            7        4        3
[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"

Clustering(4) Variable = MIRSEQ_CNMF
D4V1, survival
          sevent
clus2       0  1
  subtype1 10  1
  subtype2 10  3
subtype1 subtype2 
      11       13 
subtype1 subtype2 
       1        3 
$subtype1
TCGA-FA-8693 TCGA-FA-A4XK TCGA-FF-8042 TCGA-FF-8043 TCGA-FF-8061 TCGA-G8-6326 
        4.34        14.99        31.10        31.73        27.35        47.38 
TCGA-G8-6906 TCGA-G8-6914 TCGA-GR-A4D4 TCGA-GR-A4D5 TCGA-GR-A4D9 
      211.23       196.60        26.70        24.69        46.29 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8041 TCGA-FF-8047 TCGA-FF-8062 
        4.34         0.20         0.20        35.54         4.14        22.32 
TCGA-FM-8000 TCGA-G8-6324 TCGA-G8-6325 TCGA-G8-6907 TCGA-G8-6909 TCGA-GR-7353 
        4.57        41.16        51.98        19.56       106.09        74.10 
TCGA-GR-A4D6 
       29.95 

subtype1 subtype2 
    4.34     0.20 
subtype1 subtype2 
  211.23   106.09 
subtype1 subtype2 
   31.10    22.32 
[1] "4.3 - 211.2 (31.1)" "0.2 - 106.1 (22.3)"
[1] "hr="     "2.3e+09"
D4V2, continuous
D4V3, binary
          cls
clus       0 1
  subtype1 5 6
  subtype2 8 5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5    6
  subtype2    8    5
        clus
vv       subtype1 subtype2
  FEMALE        5        8
  MALE          6        5
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     4                         0     7
  subtype2     6                         1     6
D4V4, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            4        6
  BLACK OR AFRICAN AMERICAN        0        1
  WHITE                            7        6
[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"

Clustering(5) Variable = MIRSEQ_CHIERARCHICAL
D5V1, survival
          sevent
clus2      0 1
  subtype3 3 0
  subtype4 4 0
  subtype5 4 1
  subtype7 2 1
  subtype8 1 2
subtype3 subtype4 subtype5 subtype7 subtype8 
       3        4        5        3        3 
subtype3 subtype4 subtype5 subtype7 subtype8 
       0        0        1        1        2 
$subtype3
TCGA-FA-A4XK TCGA-G8-6914 TCGA-GR-A4D9 
       14.99       196.60        46.29 

$subtype4
TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8062 TCGA-GR-A4D6 
        0.20         0.20        22.32        29.95 

$subtype5
TCGA-FF-8041 TCGA-FF-8043 TCGA-FM-8000 TCGA-G8-6907 TCGA-GR-7353 
       35.54        31.73         4.57        19.56        74.10 

$subtype7
TCGA-FF-8047 TCGA-G8-6325 TCGA-G8-6906 
        4.14        51.98       211.23 

$subtype8
TCGA-G8-6324 TCGA-G8-6326 TCGA-G8-6909 
       41.16        47.38       106.09 

subtype3 subtype4 subtype5 subtype7 subtype8 
   14.99     0.20     4.57     4.14    41.16 
subtype3 subtype4 subtype5 subtype7 subtype8 
  196.60    29.95    74.10   211.23   106.09 
subtype3 subtype4 subtype5 subtype7 subtype8 
   46.29    11.26    31.73    51.98    47.38 
[1] "15.0 - 196.6 (46.3)" "0.2 - 29.9 (11.3)"   "4.6 - 74.1 (31.7)"  
[4] "4.1 - 211.2 (52.0)"  "41.2 - 106.1 (47.4)"
D5V2, continuous
D5V3, binary
          cls
clus       0 1
  subtype3 1 2
  subtype4 3 1
  subtype5 4 1
  subtype7 1 2
  subtype8 1 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype3    1    2
  subtype4    3    1
  subtype5    4    1
  subtype7    1    2
  subtype8    1    2
        clus
vv       subtype3 subtype4 subtype5 subtype7 subtype8
  FEMALE        1        3        4        1        1
  MALE          2        1        1        2        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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype3     1                         0     2
  subtype4     4                         0     0
  subtype5     2                         0     3
  subtype7     1                         0     2
  subtype8     0                         1     2
D5V4, multiclass
                           clus
vv                          subtype3 subtype4 subtype5 subtype7 subtype8
  ASIAN                            1        4        2        1        0
  BLACK OR AFRICAN AMERICAN        0        0        0        0        1
  WHITE                            2        0        3        2        2
[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"

Clustering(6) Variable = MIRSEQ_MATURE_CNMF
D6V1, survival
          sevent
clus2      0 1
  subtype1 6 0
  subtype2 7 2
  subtype3 7 2
subtype1 subtype2 subtype3 
       6        9        9 
subtype1 subtype2 subtype3 
       0        2        2 
$subtype1
TCGA-FA-8693 TCGA-FA-A4XK TCGA-FF-8061 TCGA-G8-6914 TCGA-GR-A4D4 TCGA-GR-A4D9 
        4.34        14.99        27.35       196.60        26.70        46.29 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8062 TCGA-G8-6324 TCGA-G8-6326 
        4.34         0.20         0.20        22.32        41.16        47.38 
TCGA-G8-6909 TCGA-GR-A4D5 TCGA-GR-A4D6 
      106.09        24.69        29.95 

$subtype3
TCGA-FF-8041 TCGA-FF-8042 TCGA-FF-8043 TCGA-FF-8047 TCGA-FM-8000 TCGA-G8-6325 
       35.54        31.10        31.73         4.14         4.57        51.98 
TCGA-G8-6906 TCGA-G8-6907 TCGA-GR-7353 
      211.23        19.56        74.10 

subtype1 subtype2 subtype3 
    4.34     0.20     4.14 
subtype1 subtype2 subtype3 
  196.60   106.09   211.23 
subtype1 subtype2 subtype3 
  27.025   24.690   31.730 
[1] "4.3 - 196.6 (27.0)" "0.2 - 106.1 (24.7)" "4.1 - 211.2 (31.7)"
D6V2, continuous
D6V3, binary
          cls
clus       0 1
  subtype1 2 4
  subtype2 5 4
  subtype3 6 3
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2    4
  subtype2    5    4
  subtype3    6    3
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        2        5        6
  MALE          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"
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     2                         0     4
  subtype2     4                         1     4
  subtype3     4                         0     5
D6V4, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            2        4        4
  BLACK OR AFRICAN AMERICAN        0        1        0
  WHITE                            4        4        5
[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"

Clustering(7) Variable = MIRSEQ_MATURE_CHIERARCHICAL
D7V1, survival
          sevent
clus2      0 1
  subtype2 3 0
  subtype3 3 0
  subtype5 2 1
  subtype7 3 1
  subtype8 2 1
subtype2 subtype3 subtype5 subtype7 subtype8 
       3        3        3        4        3 
subtype2 subtype3 subtype5 subtype7 subtype8 
       0        0        1        1        1 
$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-GR-A4D5 
        4.34         0.20        24.69 

$subtype3
TCGA-FA-A4XK TCGA-G8-6914 TCGA-GR-A4D9 
       14.99       196.60        46.29 

$subtype5
TCGA-FF-8041 TCGA-FF-8062 TCGA-G8-6909 
       35.54        22.32       106.09 

$subtype7
TCGA-FF-8043 TCGA-FM-8000 TCGA-G8-6907 TCGA-GR-7353 
       31.73         4.57        19.56        74.10 

$subtype8
TCGA-FF-8047 TCGA-G8-6325 TCGA-G8-6906 
        4.14        51.98       211.23 

subtype2 subtype3 subtype5 subtype7 subtype8 
    0.20    14.99    22.32     4.57     4.14 
subtype2 subtype3 subtype5 subtype7 subtype8 
   24.69   196.60   106.09    74.10   211.23 
subtype2 subtype3 subtype5 subtype7 subtype8 
   4.340   46.290   35.540   25.645   51.980 
[1] "0.2 - 24.7 (4.3)"    "15.0 - 196.6 (46.3)" "22.3 - 106.1 (35.5)"
[4] "4.6 - 74.1 (25.6)"   "4.1 - 211.2 (52.0)" 
D7V2, continuous
D7V3, binary
          cls
clus       0 1
  subtype2 1 2
  subtype3 1 2
  subtype5 2 1
  subtype7 3 1
  subtype8 1 2
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype2    1    2
  subtype3    1    2
  subtype5    2    1
  subtype7    3    1
  subtype8    1    2
        clus
vv       subtype2 subtype3 subtype5 subtype7 subtype8
  FEMALE        1        1        2        3        1
  MALE          2        2        1        1        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"
          vv
clus       ASIAN WHITE
  subtype2     1     2
  subtype3     1     2
  subtype5     2     1
  subtype7     1     3
  subtype8     1     2
D7V4, multiclass
       clus
vv      subtype2 subtype3 subtype5 subtype7 subtype8
  ASIAN        1        1        2        1        1
  WHITE        2        2        1        3        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"
