[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/11541278/DLBC-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/DLBC-TP/11589724/DLBC-TP.mergedcluster.txt"

nPatients in clinical file=35, in cluster file=48, common to both=35
[1]  8 35
[1] "CN_CNMF"
[1] 3
 1  2 
21 14 
 1  2 
21 14 
[1] "METHLYATION_CNMF"
[1] 3
 1  2 
17 18 
 1  2 
17 18 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2 
14 13 
 1  2 
14 13 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
 1  2  3 
13 10  4 
 1  2  3 
13 10  4 
[1] "MIRSEQ_CNMF"
[1] 3
 1  2  3  4 
11  8  5 10 
 1  2  3  4 
11  8  5 10 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
1 2 3 4 5 
9 9 5 5 6 
1 2 3 4 5 
9 9 5 5 6 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
 1  2 
13 18 
 1  2 
13 18 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
1 2 3 4 5 6 7 8 
3 4 3 4 8 3 4 2 
1 2 3 4 5 6 7 
3 4 3 4 8 3 4 
[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 35 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          410 
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-8046 TCGA-FF-8047 TCGA-FF-8061 TCGA-FF-8062 TCGA-FF-A7CQ TCGA-FF-A7CR 
         751          126          832          679          298           NA 
TCGA-FF-A7CW TCGA-FF-A7CX TCGA-FM-8000 TCGA-G8-6324 TCGA-G8-6325 TCGA-G8-6326 
         791          385          139           NA         1581         1441 
TCGA-G8-6906 TCGA-G8-6907 TCGA-G8-6909 TCGA-G8-6914 TCGA-GR-7351 TCGA-GR-7353 
          NA           NA         3227         5980         4578         2983 
TCGA-GR-A4D4 TCGA-GR-A4D5 TCGA-GR-A4D6 TCGA-GR-A4D9 TCGA-RQ-A68N 
        1099         1299         1334         1739          788 
Variable 1:'AGE':	nDistinctValues=26,	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=29,	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=2,	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=3,	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=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 17:'BATCH.NUMBER':	nDistinctValues=5,	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 35 columns, 1 survival variables, and 3 non-survival variables.
AGE, nv=26, binary=FALSE, numeric=TRUE
GENDER, nv=2, binary=FALSE, numeric=FALSE
RACE, nv=3, binary=FALSE, numeric=FALSE

Clustering(1) Variable = CN_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 15  5
  subtype2 14  0
subtype1 subtype2 
      20       14 
subtype1 subtype2 
       5        0 
$subtype1
TCGA-FA-8693 TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A7DS TCGA-FF-8041 TCGA-FF-8046 
        4.34         4.34         0.20        13.48        35.54        24.69 
TCGA-FF-8061 TCGA-FF-8062 TCGA-FF-A7CQ TCGA-FF-A7CR TCGA-FF-A7CX TCGA-G8-6324 
       27.35        22.32         9.80        10.29        12.66        41.16 
TCGA-G8-6325 TCGA-G8-6326 TCGA-G8-6906 TCGA-G8-6907 TCGA-G8-6909 TCGA-GR-7351 
       51.98        47.38       211.23        19.56       106.09       150.51 
TCGA-GR-A4D5 TCGA-GR-A4D9 
       42.71        57.17 

$subtype2
TCGA-FA-A4XK TCGA-FA-A6HO TCGA-FA-A7Q1 TCGA-FA-A82F TCGA-FF-8042 TCGA-FF-8043 
       14.99         0.20         0.72         0.82        31.10        31.73 
TCGA-FF-8047 TCGA-FF-A7CW TCGA-FM-8000 TCGA-G8-6914 TCGA-GR-7353 TCGA-GR-A4D4 
        4.14        26.01         4.57       196.60        98.07        36.13 
TCGA-GR-A4D6 TCGA-RQ-A68N 
       43.86        25.91 

subtype1 subtype2 
     0.2      0.2 
subtype1 subtype2 
  211.23   196.60 
subtype1 subtype2 
   26.02    25.96 
[1] "0.2 - 211.2 (26.0)" "0.2 - 196.6 (26.0)"
[1] "hr="     "9.3e+08"
D1V2, continuous
D1V3, binary
          cls
clus        0  1
  subtype1  9 12
  subtype2  9  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   12
  subtype2    9    5
        clus
vv       subtype1 subtype2
  FEMALE        9        9
  MALE         12        5
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     9                         1    11
  subtype2     9                         0     5
D1V4, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            9        9
  BLACK OR AFRICAN AMERICAN        1        0
  WHITE                           11        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 = METHLYATION_CNMF
D2V1, survival
          sevent
clus2       0  1
  subtype1 15  1
  subtype2 14  4
subtype1 subtype2 
      16       18 
subtype1 subtype2 
       1        4 
$subtype1
TCGA-FA-8693 TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8046 TCGA-FF-8062 
        4.34         4.34         0.20         0.20        24.69        22.32 
TCGA-FF-A7CW TCGA-G8-6324 TCGA-G8-6325 TCGA-G8-6326 TCGA-G8-6914 TCGA-GR-7351 
       26.01        41.16        51.98        47.38       196.60       150.51 
TCGA-GR-7353 TCGA-GR-A4D4 TCGA-GR-A4D5 TCGA-GR-A4D6 
       98.07        36.13        42.71        43.86 

$subtype2
TCGA-FA-A4XK TCGA-FA-A7DS TCGA-FA-A7Q1 TCGA-FA-A82F TCGA-FF-8041 TCGA-FF-8042 
       14.99        13.48         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 TCGA-RQ-A68N 
        4.57       211.23        19.56       106.09        57.17        25.91 

subtype1 subtype2 
    0.20     0.72 
subtype1 subtype2 
  196.60   211.23 
subtype1 subtype2 
  38.645   17.275 
[1] "0.2 - 196.6 (38.6)" "0.7 - 211.2 (17.3)"
[1] "hr=" "4.2"
D2V2, continuous
D2V3, binary
          cls
clus        0  1
  subtype1  8  9
  subtype2 10  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    8    9
  subtype2   10    8
        clus
vv       subtype1 subtype2
  FEMALE        8       10
  MALE          9        8
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     6                         1    10
  subtype2    12                         0     6
D2V4, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            6       12
  BLACK OR AFRICAN AMERICAN        1        0
  WHITE                           10        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(3) Variable = MRNASEQ_CNMF
D3V1, survival
          sevent
clus2       0  1
  subtype1 12  2
  subtype2 11  2
subtype1 subtype2 
      14       13 
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       150.51        36.13 
TCGA-GR-A4D9 TCGA-RQ-A68N 
       57.17        25.91 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8041 TCGA-FF-8046 TCGA-FF-8047 
        4.34         0.20         0.20        35.54        24.69         4.14 
TCGA-FF-8062 TCGA-FM-8000 TCGA-G8-6324 TCGA-G8-6907 TCGA-GR-7353 TCGA-GR-A4D5 
       22.32         4.57        41.16        19.56        98.07        42.71 
TCGA-GR-A4D6 
       43.86 

subtype1 subtype2 
    4.34     0.20 
subtype1 subtype2 
  211.23    98.07 
subtype1 subtype2 
  41.755   22.320 
[1] "4.3 - 211.2 (41.8)" "0.2 - 98.1 (22.3)" 
[1] "hr="     "2.9e+09"
D3V2, continuous
D3V3, binary
          cls
clus       0 1
  subtype1 5 9
  subtype2 9 4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5    9
  subtype2    9    4
        clus
vv       subtype1 subtype2
  FEMALE        5        9
  MALE          9        4
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     4                         0    10
  subtype2     7                         1     5
D3V4, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            4        7
  BLACK OR AFRICAN AMERICAN        0        1
  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(4) Variable = MRNASEQ_CHIERARCHICAL
D4V1, survival
          sevent
clus2       0  1
  subtype1 11  2
  subtype2  8  2
  subtype3  4  0
subtype1 subtype2 subtype3 
      13       10        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       150.51 
TCGA-RQ-A68N 
       25.91 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8046 TCGA-FF-8047 TCGA-FM-8000 
        4.34         0.20         0.20        24.69         4.14         4.57 
TCGA-G8-6324 TCGA-G8-6907 TCGA-GR-7353 TCGA-GR-A4D6 
       41.16        19.56        98.07        43.86 

$subtype3
TCGA-FA-A4XK TCGA-GR-A4D4 TCGA-GR-A4D5 TCGA-GR-A4D9 
       14.99        36.13        42.71        57.17 

subtype1 subtype2 subtype3 
    4.34     0.20    14.99 
subtype1 subtype2 subtype3 
  211.23    98.07    57.17 
subtype1 subtype2 subtype3 
  35.540   12.065   39.420 
[1] "4.3 - 211.2 (35.5)" "0.2 - 98.1 (12.1)"  "15.0 - 57.2 (39.4)"
D4V2, continuous
D4V3, binary
          cls
clus       0 1
  subtype1 5 8
  subtype2 6 4
  subtype3 3 1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    5    8
  subtype2    6    4
  subtype3    3    1
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        5        6        3
  MALE          8        4        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     8
  subtype2     5                         1     4
  subtype3     1                         0     3
D4V4, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            5        5        1
  BLACK OR AFRICAN AMERICAN        0        1        0
  WHITE                            8        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(5) Variable = MIRSEQ_CNMF
D5V1, survival
          sevent
clus2       0  1
  subtype1 10  1
  subtype2  6  1
  subtype3  4  1
  subtype4  8  2
subtype1 subtype2 subtype3 subtype4 
      11        7        5       10 
subtype1 subtype2 subtype3 subtype4 
       1        1        1        2 
$subtype1
TCGA-FA-8693 TCGA-FA-A4XK TCGA-FA-A7Q1 TCGA-FA-A82F TCGA-FF-8042 TCGA-FF-8046 
        4.34        14.99         0.72         0.82        31.10        24.69 
TCGA-G8-6326 TCGA-G8-6906 TCGA-G8-6914 TCGA-GR-A4D9 TCGA-RQ-A68N 
       47.38       211.23       196.60        57.17        25.91 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8062 TCGA-G8-6324 TCGA-GR-A4D5 
        4.34         0.20         0.20        22.32        41.16        42.71 
TCGA-GR-A4D6 
       43.86 

$subtype3
TCGA-FA-A7DS TCGA-FF-A7CQ TCGA-FF-A7CR TCGA-FF-A7CW TCGA-FF-A7CX 
       13.48         9.80        10.29        26.01        12.66 

$subtype4
TCGA-FF-8041 TCGA-FF-8043 TCGA-FF-8047 TCGA-FF-8061 TCGA-FM-8000 TCGA-G8-6325 
       35.54        31.73         4.14        27.35         4.57        51.98 
TCGA-G8-6907 TCGA-G8-6909 TCGA-GR-7353 TCGA-GR-A4D4 
       19.56       106.09        98.07        36.13 

subtype1 subtype2 subtype3 subtype4 
    0.72     0.20     9.80     4.14 
subtype1 subtype2 subtype3 subtype4 
  211.23    43.86    26.01   106.09 
subtype1 subtype2 subtype3 subtype4 
  25.910   22.320   12.660   33.635 
[1] "0.7 - 211.2 (25.9)" "0.2 - 43.9 (22.3)"  "9.8 - 26.0 (12.7)" 
[4] "4.1 - 106.1 (33.6)"
D5V2, continuous
D5V3, binary
          cls
clus       0 1
  subtype1 4 7
  subtype2 6 2
  subtype3 1 4
  subtype4 6 4
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    4    7
  subtype2    6    2
  subtype3    1    4
  subtype4    6    4
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        4        6        1        6
  MALE          7        2        4        4
[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     5                         0     6
  subtype2     4                         1     3
  subtype3     5                         0     0
  subtype4     4                         0     6
D5V4, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            5        4        5        4
  BLACK OR AFRICAN AMERICAN        0        1        0        0
  WHITE                            6        3        0        6
[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"

Clustering(6) Variable = MIRSEQ_CHIERARCHICAL
D6V1, survival
          sevent
clus2      0 1
  subtype1 8 1
  subtype2 6 2
  subtype3 5 0
  subtype4 4 1
  subtype5 5 1
subtype1 subtype2 subtype3 subtype4 subtype5 
       9        8        5        5        6 
subtype1 subtype2 subtype3 subtype4 subtype5 
       1        2        0        1        1 
$subtype1
TCGA-FA-8693 TCGA-FF-8042 TCGA-FF-8046 TCGA-FF-8061 TCGA-FF-A7CX TCGA-G8-6325 
        4.34        31.10        24.69        27.35        12.66        51.98 
TCGA-G8-6326 TCGA-G8-6906 TCGA-GR-A4D4 
       47.38       211.23        36.13 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FA-A6HO TCGA-FF-8062 TCGA-G8-6324 TCGA-G8-6909 
        4.34         0.20         0.20        22.32        41.16       106.09 
TCGA-GR-A4D5 TCGA-GR-A4D6 
       42.71        43.86 

$subtype3
TCGA-FA-A4XK TCGA-FA-A7Q1 TCGA-FA-A82F TCGA-G8-6914 TCGA-RQ-A68N 
       14.99         0.72         0.82       196.60        25.91 

$subtype4
TCGA-FA-A7DS TCGA-FF-A7CQ TCGA-FF-A7CR TCGA-FF-A7CW TCGA-GR-A4D9 
       13.48         9.80        10.29        26.01        57.17 

$subtype5
TCGA-FF-8041 TCGA-FF-8043 TCGA-FF-8047 TCGA-FM-8000 TCGA-G8-6907 TCGA-GR-7353 
       35.54        31.73         4.14         4.57        19.56        98.07 

subtype1 subtype2 subtype3 subtype4 subtype5 
    4.34     0.20     0.72     9.80     4.14 
subtype1 subtype2 subtype3 subtype4 subtype5 
  211.23   106.09   196.60    57.17    98.07 
subtype1 subtype2 subtype3 subtype4 subtype5 
  31.100   31.740   14.990   13.480   25.645 
[1] "4.3 - 211.2 (31.1)" "0.2 - 106.1 (31.7)" "0.7 - 196.6 (15.0)"
[4] "9.8 - 57.2 (13.5)"  "4.1 - 98.1 (25.6)" 
D6V2, continuous
D6V3, binary
          cls
clus       0 1
  subtype1 2 7
  subtype2 6 3
  subtype3 2 3
  subtype4 2 3
  subtype5 5 1
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2    7
  subtype2    6    3
  subtype3    2    3
  subtype4    2    3
  subtype5    5    1
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5
  FEMALE        2        6        2        2        5
  MALE          7        3        3        3        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     4                         0     5
  subtype2     4                         1     4
  subtype3     3                         0     2
  subtype4     4                         0     1
  subtype5     3                         0     3
D6V4, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN                            4        4        3        4        3
  BLACK OR AFRICAN AMERICAN        0        1        0        0        0
  WHITE                            5        4        2        1        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"

Clustering(7) Variable = MIRSEQ_MATURE_CNMF
D7V1, survival
          sevent
clus2       0  1
  subtype1 12  1
  subtype2 13  4
subtype1 subtype2 
      13       17 
subtype1 subtype2 
       1        4 
$subtype1
TCGA-FA-8693 TCGA-FA-A4XK TCGA-FA-A7DS TCGA-FA-A7Q1 TCGA-FA-A82F TCGA-FF-8042 
        4.34        14.99        13.48         0.72         0.82        31.10 
TCGA-FF-8046 TCGA-FF-8061 TCGA-FF-A7CW TCGA-FF-A7CX TCGA-G8-6906 TCGA-G8-6914 
       24.69        27.35        26.01        12.66       211.23       196.60 
TCGA-RQ-A68N 
       25.91 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-FF-8041 TCGA-FF-8043 TCGA-FF-8047 TCGA-FF-8062 
        4.34         0.20        35.54        31.73         4.14        22.32 
TCGA-FF-A7CR TCGA-FM-8000 TCGA-G8-6324 TCGA-G8-6325 TCGA-G8-6326 TCGA-G8-6907 
       10.29         4.57        41.16        51.98        47.38        19.56 
TCGA-G8-6909 TCGA-GR-7353 TCGA-GR-A4D4 TCGA-GR-A4D5 TCGA-GR-A4D6 
      106.09        98.07        36.13        42.71        43.86 

subtype1 subtype2 
    0.72     0.20 
subtype1 subtype2 
  211.23   106.09 
subtype1 subtype2 
   24.69    35.54 
[1] "0.7 - 211.2 (24.7)" "0.2 - 106.1 (35.5)"
[1] "hr="     "1.6e+09"
D7V2, continuous
D7V3, binary
          cls
clus        0  1
  subtype1  4  9
  subtype2 11  7
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    4    9
  subtype2   11    7
        clus
vv       subtype1 subtype2
  FEMALE        4       11
  MALE          9        7
[1] 2 2
[1] FALSE
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     9                         0     4
  subtype2     7                         1    10
D7V4, multiclass
                           clus
vv                          subtype1 subtype2
  ASIAN                            9        7
  BLACK OR AFRICAN AMERICAN        0        1
  WHITE                            4       10
[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(8) Variable = MIRSEQ_MATURE_CHIERARCHICAL
D8V1, survival
          sevent
clus2      0 1
  subtype1 3 0
  subtype2 3 0
  subtype3 3 0
  subtype4 3 1
  subtype5 7 1
  subtype6 2 1
  subtype7 3 1
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
       3        3        3        4        8        3        4 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
       0        0        0        1        1        1        1 
$subtype1
TCGA-FA-8693 TCGA-FA-A82F TCGA-FF-8062 
        4.34         0.82        22.32 

$subtype2
TCGA-FA-A4BB TCGA-FA-A6HN TCGA-GR-A4D5 
        4.34         0.20        42.71 

$subtype3
TCGA-FA-A4XK TCGA-G8-6914 TCGA-RQ-A68N 
       14.99       196.60        25.91 

$subtype4
TCGA-FA-A7DS TCGA-FF-A7CR TCGA-FF-A7CW TCGA-FF-A7CX 
       13.48        10.29        26.01        12.66 

$subtype5
TCGA-FA-A7Q1 TCGA-FF-8042 TCGA-FF-8043 TCGA-FF-8046 TCGA-FF-8047 TCGA-FF-8061 
        0.72        31.10        31.73        24.69         4.14        27.35 
TCGA-G8-6906 TCGA-GR-7353 
      211.23        98.07 

$subtype6
TCGA-FF-8041 TCGA-G8-6325 TCGA-G8-6909 
       35.54        51.98       106.09 

$subtype7
TCGA-FM-8000 TCGA-G8-6907 TCGA-GR-A4D4 TCGA-GR-A4D6 
        4.57        19.56        36.13        43.86 

subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
    0.82     0.20    14.99    10.29     0.72    35.54     4.57 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
   22.32    42.71   196.60    26.01   211.23   106.09    43.86 
subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7 
   4.340    4.340   25.910   13.070   29.225   51.980   27.845 
[1] "0.8 - 22.3 (4.3)"    "0.2 - 42.7 (4.3)"    "15.0 - 196.6 (25.9)"
[4] "10.3 - 26.0 (13.1)"  "0.7 - 211.2 (29.2)"  "35.5 - 106.1 (52.0)"
[7] "4.6 - 43.9 (27.8)"  
D8V2, continuous
D8V3, binary
          cls
clus       0 1
  subtype1 2 1
  subtype2 2 2
  subtype3 0 3
  subtype4 1 3
  subtype5 4 4
  subtype6 1 2
  subtype7 4 0
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2    1
  subtype2    2    2
  subtype3    0    3
  subtype4    1    3
  subtype5    4    4
  subtype6    1    2
  subtype7    4    0
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  FEMALE        2        2        0        1        4        1        4
  MALE          1        2        3        3        4        2        0
[1] 2 7
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
          vv
clus       ASIAN WHITE
  subtype1     2     1
  subtype2     1     3
  subtype3     1     2
  subtype4     4     0
  subtype5     6     2
  subtype6     1     2
  subtype7     1     3
D8V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4 subtype5 subtype6 subtype7
  ASIAN        2        1        1        4        6        1        1
  WHITE        1        3        2        0        2        2        3
[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"
