[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"        "-oTESCA-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/ESCA-TP/11541396/ESCA-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/ESCA-TP/11589242/ESCA-TP.mergedcluster.txt"

nPatients in clinical file=151, in cluster file=185, common to both=151
[1]   8 151
[1] "CN_CNMF"
[1] 3
 1  2  3 
59 35 56 
 1  2  3 
59 35 56 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3 
68 28 55 
 1  2  3 
68 28 55 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2  3  4  5 
43  8 18 29 10 
 1  2  3  4  5 
43  8 18 29 10 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
 1  2  3 
36 60 12 
 1  2  3 
36 60 12 
[1] "MIRSEQ_CNMF"
[1] 3
 1  2  3 
76 63 11 
 1  2  3 
76 63 11 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
 1  2  3  4 
56 24 46 24 
 1  2  3  4 
56 24 46 24 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
 1  2  3  4 
60 47 32  7 
 1  2  3  4 
60 47 32  7 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
 1  2  3 
57 20 69 
 1  2  3 
57 20 69 
[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] "RADIATIONS.RADIATION.REGIMENINDICATION"
[12] "NUMBERPACKYEARSSMOKED"                 
[13] "RACE"                                  
[14] "ETHNICITY"                             
[15] "BATCHNUMBER"                           

Input Data has 15 rows and 151 columns.

[1] "Batch" "15"   
[1] "Last Follow UP"
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
          NA           NA           NA           NA           NA           NA 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GQ TCGA-2H-A9GR 
          NA           NA           NA           NA           NA           NA 
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC 
        1012          611           NA          632           80          612 
TCGA-IG-A4P3 TCGA-IG-A4QS TCGA-IG-A4QT TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 
           1            8           30           16          518           NA 
TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A7DP TCGA-IG-A8O2 TCGA-IG-A97H 
         712           11            4          452           14           13 
TCGA-IG-A97I TCGA-JY-A6F8 TCGA-JY-A6FA TCGA-JY-A6FB TCGA-JY-A6FD TCGA-JY-A6FE 
          NA         3714           NA         1837         2069           NA 
TCGA-JY-A6FG TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A939 TCGA-JY-A93C TCGA-JY-A93D 
          NA         1301          773          471          705          769 
TCGA-JY-A93E TCGA-JY-A93F TCGA-KH-A6WC TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43H 
         550          535          189           96          105           NA 
TCGA-L5-A43J TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH 
          NA          272          107          112          102          593 
TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4OM TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP 
         267          195          124           NA          101          218 
TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW 
          NA           NA          935           NA          882           NA 
TCGA-L5-A4OX TCGA-L5-A88S TCGA-L5-A88T TCGA-L5-A88V TCGA-L5-A88W TCGA-L5-A88Y 
          NA          211          265           79           NA           11 
TCGA-L5-A88Z TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NG 
         225          120           92         1688           NA         1094 
TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NK TCGA-L5-A8NL TCGA-L5-A8NM 
          NA           NA          501          412          402           NA 
TCGA-L5-A8NN TCGA-L5-A8NQ TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU 
         165           NA          265          408          825           NA 
TCGA-L5-A8NV TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M 
          NA           NA          315            2          318            5 
TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49P TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U 
           2           10           NA            3            4            2 
TCGA-LN-A49V TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A1 TCGA-LN-A4A2 
           3            2            3            2           NA            4 
TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
           2            3            3            3            2            2 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-LN-A7HV TCGA-LN-A7HW 
           3            2            6           36           NA           NA 
TCGA-LN-A7HX TCGA-LN-A7HY TCGA-LN-A7HZ TCGA-M9-A5M8 TCGA-Q9-A6FU TCGA-Q9-A6FW 
          NA           NA           NA          536           NA          115 
TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG 
          NA           NA           NA          447           NA          900 
TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-S8-A6BV TCGA-S8-A6BW 
          NA         1641           NA           NA          267          426 
TCGA-V5-A7RB TCGA-V5-A7RC TCGA-V5-A7RE TCGA-V5-AASV TCGA-V5-AASW TCGA-V5-AASX 
          NA           NA          146          258          248          135 
TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8Q7 TCGA-VR-AA4G TCGA-VR-AA7D TCGA-VR-AA7I 
          NA           NA         1117          366           NA           NA 
TCGA-ZR-A9CJ 
         551 
Variable 1:'AGE':	nDistinctValues=46,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 2:'VITALSTATUS':	nDistinctValues=2,	numeric=TRUE,	binary=TRUE,	exclude=FALSE.
Variable 3:'DAYSTODEATH':	nDistinctValues=53,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
Variable 4:'DAYSTOLASTFOLLOWUP':	nDistinctValues=78,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
Variable 5:'NEOPLASM.DISEASESTAGE':	nDistinctValues=12,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 6:'PATHOLOGY.T.STAGE':	nDistinctValues=6,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 7:'PATHOLOGY.N.STAGE':	nDistinctValues=5,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 8:'PATHOLOGY.M.STAGE':	nDistinctValues=4,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 9:'DCCUPLOADDAY':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 10:'GENDER':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 11:'RADIATIONS.RADIATION.REGIMENINDICATION':	nDistinctValues=1,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 12:'NUMBERPACKYEARSSMOKED':	nDistinctValues=38,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 13:'RACE':	nDistinctValues=3,	numeric=FALSE,	binary=FALSE,	exclude=FALSE.
Variable 14:'ETHNICITY':	nDistinctValues=2,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
Variable 15:'BATCH.NUMBER':	nDistinctValues=11,	numeric=FALSE,	binary=FALSE,	exclude=TRUE.
[1] "rownames(nsurv.mat)"
[1] "AGE"                   "NEOPLASM.DISEASESTAGE" "PATHOLOGY.T.STAGE"    
[4] "PATHOLOGY.N.STAGE"     "PATHOLOGY.M.STAGE"     "GENDER"               
[7] "NUMBERPACKYEARSSMOKED" "RACE"                 
[1] "TUMOR.?STAGE"
[1] "TUMOR.?GRADE"
[1] "PATHOLOGY.T" "3"          
[1] "PATHOLOGY.N" "4"          
Output Data has 151 columns, 1 survival variables, and 8 non-survival variables.
AGE, nv=46, binary=FALSE, numeric=TRUE
NEOPLASM.DISEASESTAGE, nv=12, binary=FALSE, numeric=FALSE
PATHOLOGY.T.STAGE, nv=5, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.T',vnm)"
vv
T0 T1 T2 T3 T4 
 1 25 33 75  4 
[1] "table(vv)"
vv
T0+T1    T2    T3    T4 
   26    33    75     4 
$ClinVariableName
[1] "PATHOLOGY.T.STAGE"

$Table
vv
T0 T1 T2 T3 T4 
 1 25 33 75  4 

$nClasses
[1] 4

$ClinVariableType
[1] "multiclass(4)"


T0+T1    T2    T3    T4 
   26    33    75     4 
PATHOLOGY.N.STAGE, nv=4, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.N',vnm)"
vv
N0 N1 N2 N3 
64 55 11  6 
[1] "table(vv)"
vv
N0 N1 N2 N3 
64 55 11  6 
$ClinVariableName
[1] "PATHOLOGY.N.STAGE"

$Table
vv
N0 N1 N2 N3 
64 55 11  6 

$nClasses
[1] 4

$ClinVariableType
[1] "multiclass(4)"


N0 N1 N2 N3 
64 55 11  6 
PATHOLOGY.M.STAGE, nv=4, binary=FALSE, numeric=FALSE
GENDER, nv=2, binary=FALSE, numeric=FALSE
NUMBERPACKYEARSSMOKED, nv=38, binary=FALSE, numeric=TRUE
RACE, nv=3, binary=FALSE, numeric=FALSE

Clustering(1) Variable = CN_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 31 28
  subtype2 25  9
  subtype3 32 17
subtype1 subtype2 subtype3 
      59       34       49 
subtype1 subtype2 subtype3 
      28        9       17 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL 
       25.78        31.27        14.30        58.55         7.63         5.92 
TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GQ TCGA-2H-A9GR TCGA-IG-A3QL TCGA-IG-A4QS 
       13.94         8.94         4.21        32.45        20.09         0.26 
TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43M TCGA-L5-A4OE 
      122.10        60.39        42.77        23.18         8.94         3.52 
TCGA-L5-A4OH TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OT 
       19.50        18.35         7.17         1.38         3.16         4.90 
TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A8NE 
        7.13         7.43         2.60         0.36         3.95        55.50 
TCGA-L5-A8NF TCGA-L5-A8NG TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NN 
        2.66        35.97        12.92        13.48        16.47         5.42 
TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-LN-A49L 
        8.71        13.41        27.12        46.09        10.36        10.45 
TCGA-LN-A49U TCGA-LN-A49V TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ 
        0.07         0.10        17.62         8.02         7.59         5.06 
TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-RE-A7BO TCGA-S8-A6BV 
       14.70        29.59         6.35        53.95         7.00         8.78 
TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW TCGA-VR-A8Q7 TCGA-ZR-A9CJ 
        5.29         4.80         8.15        36.72        18.12 

$subtype2
TCGA-2H-A9GO TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A6FD TCGA-JY-A6FG TCGA-JY-A938 
       16.24         0.99        14.86        68.02        41.52        25.41 
TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E TCGA-JY-A93F TCGA-KH-A6WC TCGA-L5-A43C 
       15.48        25.28        18.08        17.59         6.21         3.16 
TCGA-L5-A43E TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4OO 
        3.45         3.68         3.35         8.78         6.41         3.32 
TCGA-L5-A4OS TCGA-L5-A4OU TCGA-L5-A88T TCGA-L5-A88W TCGA-L5-A893 TCGA-L5-A8NK 
       30.74        29.00         8.71        25.12         3.02        13.55 
TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NQ TCGA-L5-A8NU TCGA-LN-A49X TCGA-Q9-A6FW 
       13.22         7.76        21.37        83.24         0.10         3.78 
TCGA-R6-A6L6 TCGA-R6-A6Y2 TCGA-V5-AASV TCGA-V5-AASX 
        7.04         9.30         8.48         4.44 

$subtype3
TCGA-IG-A3I8 TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC TCGA-IG-A4P3 
       33.27         0.85        20.78         2.63        20.12         0.03 
TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS 
        0.53        17.03         0.79        23.41         0.36         0.13 
TCGA-IG-A8O2 TCGA-IG-A97H TCGA-JY-A6FA TCGA-JY-A6FE TCGA-L5-A43H TCGA-L5-A43J 
        0.46         0.43        44.75         3.68         0.30         4.31 
TCGA-L5-A4OM TCGA-L5-A88S TCGA-L5-A88Z TCGA-L5-A8NV TCGA-LN-A49K TCGA-LN-A49M 
        4.08         6.94         7.40        52.57         0.07         0.16 
TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49W TCGA-LN-A49Y 
        0.07         0.33         0.10         0.13         0.07         0.07 
TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 
        0.13         0.07         0.10         0.10         0.10         0.07 
TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU 
        0.07         0.10         0.07         0.20         1.18         5.16 
TCGA-S8-A6BW TCGA-V5-A7RC TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-AA4G TCGA-VR-AA7D 
       14.01         3.42        18.31         8.12        12.03         9.17 
TCGA-VR-AA7I 
       15.91 

subtype1 subtype2 subtype3 
    0.07     0.10     0.03 
subtype1 subtype2 subtype3 
  122.10    83.24    52.57 
subtype1 subtype2 subtype3 
    8.94     9.04     0.53 
[1] "0.1 - 122.1 (8.9)" "0.1 - 83.2 (9.0)"  "0.0 - 52.6 (0.5)" 
D1V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       4        2        2        0         5        11        12
  subtype2       4        1        1        0         9         7         2
  subtype3       0        1        3        1        21         8         9
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          3          3          2        2         1
  subtype2          2          1          3        0         1
  subtype3          6          4          1        1         0
D1V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           4        4        0
  STAGE IA          2        1        1
  STAGE IB          2        1        3
  STAGE II          0        0        1
  STAGE IIA         5        9       21
  STAGE IIB        11        7        8
  STAGE III        12        2        9
  STAGE IIIA        3        2        6
  STAGE IIIB        3        1        4
  STAGE IIIC        2        3        1
  STAGE IV          2        0        1
  STAGE IVA         1        1        0
[1] 12  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       T0+T1 T2 T3 T4
  subtype1    15  7 29  0
  subtype2     7  7 16  1
  subtype3     4 19 29  3
D1V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       15        7        4
  T2           7        7       19
  T3          29       16       29
  T4           0        1        3
[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       N0 N1 N2 N3
  subtype1 18 26  5  2
  subtype2 17  9  1  3
  subtype3 29 19  5  1
D1V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       18       17       29
  N1       26        9       19
  N2        5        1        5
  N3        2        3        1
[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       M0 M1 M1A MX
  subtype1 36  1   2 10
  subtype2 25  0   1  4
  subtype3 50  1   0  3
D1V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        36       25       50
  M1         1        0        1
  M1A        2        1        0
  MX        10        4        3
[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"
D1V7, binary
          cls
clus        0  1
  subtype1  6 53
  subtype2  9 26
  subtype3  6 50
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    6   53
  subtype2    9   26
  subtype3    6   50
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        6        9        6
  MALE         53       26       50
[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"
D1V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     4                         0    40
  subtype2     3                         1    30
  subtype3    31                         1    23
D1V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            4        3       31
  BLACK OR AFRICAN AMERICAN        0        1        1
  WHITE                           40       30       23
[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(2) Variable = METHLYATION_CNMF
D2V1, survival
          sevent
clus2       0  1
  subtype1 39 29
  subtype2 18  8
  subtype3 31 18
subtype1 subtype2 subtype3 
      68       26       49 
subtype1 subtype2 subtype3 
      29        8       18 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GR TCGA-IG-A4QS TCGA-JY-A6F8 
        5.92        13.94         8.94        32.45         0.26       122.10 
TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A93C TCGA-JY-A93D TCGA-JY-A93E 
       60.39        42.77        25.41        23.18        25.28        18.08 
TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH 
        3.16         3.45         3.52         3.68         3.35        19.50 
TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OR TCGA-L5-A4OT 
        8.78         6.41        18.35         7.17         3.16         4.90 
TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 
       29.00         7.13         7.43         2.60         0.36         3.95 
TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NG TCGA-L5-A8NH TCGA-L5-A8NI 
        3.02        55.50         2.66        35.97        12.92        13.48 
TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NS 
       16.47        13.22         7.76         5.42         8.71        13.41 
TCGA-L5-A8NT TCGA-L5-A8NV TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-Q9-A6FW 
       27.12        52.57        46.09        10.36        17.62         3.78 
TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ 
        8.02         7.59         5.06        14.70        29.59         6.35 
TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW 
        9.30         7.00         8.78         5.29         4.80         8.15 
TCGA-V5-AASX TCGA-ZR-A9CJ 
        4.44        18.12 

$subtype2
TCGA-2H-A9GO TCGA-IG-A3YA TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A4QT TCGA-IG-A5B8 
       16.24        20.78        20.12         0.03         0.99         0.79 
TCGA-IG-A5S3 TCGA-IG-A7DP TCGA-IG-A97H TCGA-JY-A939 TCGA-KH-A6WC TCGA-L5-A43M 
       23.41        14.86         0.43        15.48         6.21         8.94 
TCGA-L5-A4OO TCGA-L5-A4OQ TCGA-L5-A4OS TCGA-L5-A88S TCGA-L5-A88T TCGA-L5-A8NQ 
        3.32         1.38        30.74         6.94         8.71        21.37 
TCGA-L5-A8NU TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A3 TCGA-LN-A4A5 TCGA-R6-A6L6 
       83.24         0.07         0.10         0.07         0.10         7.04 
TCGA-R6-A6Y0 TCGA-VR-A8Q7 
       53.95        36.72 

$subtype3
TCGA-2H-A9GQ TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YB TCGA-IG-A50L 
        4.21        33.27        20.09         0.85         2.63         0.53 
TCGA-IG-A51D TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-JY-A6FD 
       17.03         0.36         0.13         0.46        44.75        68.02 
TCGA-JY-A6FE TCGA-JY-A6FG TCGA-JY-A93F TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A4OM 
        3.68        41.52        17.59         0.30         4.31         4.08 
TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M 
       25.12         7.40        13.55         0.07        10.45         0.16 
TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49V 
        0.07         0.33         0.10         0.13         0.07         0.10 
TCGA-LN-A49Y TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
        0.07         0.13         0.10         0.10         0.07         0.07 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW 
        0.10         0.07         0.20         1.18         5.16        14.01 
TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-AA4G TCGA-VR-AA7D 
        3.42         8.48        18.31         8.12        12.03         9.17 
TCGA-VR-AA7I 
       15.91 

subtype1 subtype2 subtype3 
    0.26     0.03     0.07 
subtype1 subtype2 subtype3 
  122.10    83.24    68.02 
subtype1 subtype2 subtype3 
   8.860    7.875    2.630 
[1] "0.3 - 122.1 (8.9)" "0.0 - 83.2 (7.9)"  "0.1 - 68.0 (2.6)" 
D2V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       8        2        2        0         4        13        13
  subtype2       0        1        2        0         7         5         3
  subtype3       0        1        2        1        24         8         8
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          4          4        2         1
  subtype2          5          0          1        0         1
  subtype3          4          4          1        1         0
D2V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           8        0        0
  STAGE IA          2        1        1
  STAGE IB          2        2        2
  STAGE II          0        0        1
  STAGE IIA         4        7       24
  STAGE IIB        13        5        8
  STAGE III        13        3        8
  STAGE IIIA        2        5        4
  STAGE IIIB        4        0        4
  STAGE IIIC        4        1        1
  STAGE IV          2        0        1
  STAGE IVA         1        1        0
[1] 12  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       T0+T1 T2 T3 T4
  subtype1    20  7 31  0
  subtype2     2  7 15  2
  subtype3     4 19 29  2
D2V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       20        2        4
  T2           7        7       19
  T3          31       15       29
  T4           0        2        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       N0 N1 N2 N3
  subtype1 21 29  4  4
  subtype2 11 10  2  1
  subtype3 32 16  5  1
D2V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       21       11       32
  N1       29       10       16
  N2        4        2        5
  N3        4        1        1
[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       M0 M1 M1A MX
  subtype1 43  1   2  9
  subtype2 21  0   1  4
  subtype3 48  1   0  4
D2V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        43       21       48
  M1         1        0        1
  M1A        2        1        0
  MX         9        4        4
[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"
D2V7, binary
          cls
clus        0  1
  subtype1  9 59
  subtype2  4 24
  subtype3  8 47
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   59
  subtype2    4   24
  subtype3    8   47
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        9        4        8
  MALE         59       24       47
[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"
D2V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    53
  subtype2     7                         0    19
  subtype3    30                         2    21
D2V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        7       30
  BLACK OR AFRICAN AMERICAN        0        0        2
  WHITE                           53       19       21
[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(3) Variable = MRNASEQ_CNMF
D3V1, survival
          sevent
clus2       0  1
  subtype1 27 16
  subtype2  6  2
  subtype3 10  5
  subtype4 17  9
  subtype5  7  2
subtype1 subtype2 subtype3 subtype4 subtype5 
      43        8       15       26        9 
subtype1 subtype2 subtype3 subtype4 subtype5 
      16        2        5        9        2 
$subtype1
TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-L5-A43C TCGA-L5-A43E 
        0.26       122.10        60.39        42.77         3.16         3.45 
TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI 
        8.94         3.52         3.68         3.35        19.50         8.78 
TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR 
        6.41        18.35         3.32         7.17         1.38         3.16 
TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V 
       30.74         4.90        29.00         7.13         7.43         2.60 
TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NJ TCGA-L5-A8NU TCGA-L7-A6VZ 
        0.36         3.95         3.02        16.47        83.24        10.36 
TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 
       17.62         8.02         7.59         5.06        14.70         7.04 
TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB 
       29.59         6.35         9.30         7.00         8.78         5.29 
TCGA-V5-A7RE 
        4.80 

$subtype2
TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-KH-A6WC TCGA-L5-A88T TCGA-L5-A8NQ TCGA-LN-A49S 
       20.12         0.03         6.21         8.71        21.37         0.13 
TCGA-Q9-A6FW TCGA-R6-A6Y0 
        3.78        53.95 

$subtype3
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A625 TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-L5-A43H 
       33.27        20.09         0.36         0.46        44.75         0.30 
TCGA-L5-A4OM TCGA-L5-A88Z TCGA-LN-A49K TCGA-LN-A49R TCGA-LN-A49Y TCGA-LN-A4A4 
        4.08         7.40         0.07         0.10         0.07         0.10 
TCGA-LN-A4MQ TCGA-S8-A6BW TCGA-VR-A8EW 
        0.10        14.01         8.12 

$subtype4
TCGA-IG-A3Y9 TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A6QS TCGA-JY-A6FD 
        0.85         0.53        17.03         0.79         0.13        68.02 
TCGA-JY-A6FE TCGA-JY-A6FG TCGA-L5-A43J TCGA-L5-A88S TCGA-L5-A88W TCGA-LN-A49M 
        3.68        41.52         4.31         6.94        25.12         0.16 
TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49U TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A2 
        0.07         0.33         0.07         0.07         0.10         0.13 
TCGA-LN-A4A3 TCGA-LN-A4A6 TCGA-LN-A4A9 TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 
        0.07         0.10         0.07         0.07         0.20         1.18 
TCGA-Q9-A6FU TCGA-VR-A8EU 
        5.16        18.31 

$subtype5
TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4QT TCGA-IG-A5S3 TCGA-IG-A7DP TCGA-LN-A49L 
       20.78         2.63         0.99        23.41        14.86        10.45 
TCGA-LN-A49V TCGA-LN-A4A5 TCGA-LN-A4A8 
        0.10         0.10         0.07 

subtype1 subtype2 subtype3 subtype4 subtype5 
    0.26     0.03     0.07     0.07     0.07 
subtype1 subtype2 subtype3 subtype4 subtype5 
  122.10    53.95    44.75    68.02    23.41 
subtype1 subtype2 subtype3 subtype4 subtype5 
    7.13     7.46     0.46     0.43     2.63 
[1] "0.3 - 122.1 (7.1)" "0.0 - 54.0 (7.5)"  "0.1 - 44.8 (0.5)" 
[4] "0.1 - 68.0 (0.4)"  "0.1 - 23.4 (2.6)" 
D3V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        1        0         3         7         2
  subtype2       0        1        0        0         2         2         0
  subtype3       0        1        1        0         7         2         4
  subtype4       0        0        2        1        13         5         4
  subtype5       0        0        0        0         5         1         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1          2          2          3        1
  subtype2          1          1          0        0
  subtype3          0          3          0        0
  subtype4          2          1          0        1
  subtype5          3          0          0        0
D3V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4 subtype5
  STAGE I           7        0        0        0        0
  STAGE IA          2        1        1        0        0
  STAGE IB          1        0        1        2        0
  STAGE II          0        0        0        1        0
  STAGE IIA         3        2        7       13        5
  STAGE IIB         7        2        2        5        1
  STAGE III         2        0        4        4        1
  STAGE IIIA        2        1        0        2        3
  STAGE IIIB        2        1        3        1        0
  STAGE IIIC        3        0        0        0        0
  STAGE IV          1        0        0        1        0
[1] 11  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       T0+T1 T2 T3 T4
  subtype1    15  6 13  0
  subtype2     1  3  3  0
  subtype3     2  4 12  0
  subtype4     2 10 16  1
  subtype5     0  3  5  2
D3V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4 subtype5
  T0+T1       15        1        2        2        0
  T2           6        3        4       10        3
  T3          13        3       12       16        5
  T4           0        0        0        1        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       N0 N1 N2 N3
  subtype1 14 13  4  3
  subtype2  3  3  1  0
  subtype3  9  6  3  0
  subtype4 18 10  1  0
  subtype5  7  2  0  0
D3V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4 subtype5
  N0       14        3        9       18        7
  N1       13        3        6       10        2
  N2        4        1        3        1        0
  N3        3        0        0        0        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       M0 M1 M1A MX
  subtype1 20  0   1 10
  subtype2  7  0   0  0
  subtype3 16  0   0  1
  subtype4 25  1   0  3
  subtype5  9  0   0  1
D3V6, multiclass
     clus
vv    subtype1 subtype2 subtype3 subtype4 subtype5
  M0        20        7       16       25        9
  M1         0        0        0        1        0
  M1A        1        0        0        0        0
  MX        10        0        1        3        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"
D3V7, binary
          cls
clus        0  1
  subtype1  9 34
  subtype2  0  8
  subtype3  3 15
  subtype4  2 27
  subtype5  2  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   34
  subtype2    0    8
  subtype3    3   15
  subtype4    2   27
  subtype5    2    8
        clus
vv       subtype1 subtype2 subtype3 subtype4 subtype5
  FEMALE        9        0        3        2        2
  MALE         34        8       15       27        8
[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"
D3V8, continuous
          vv
clus       ASIAN WHITE
  subtype1     0    39
  subtype2     1     7
  subtype3    12     6
  subtype4    18    11
  subtype5     5     5
D3V9, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4 subtype5
  ASIAN        0        1       12       18        5
  WHITE       39        7        6       11        5
[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(4) Variable = MRNASEQ_CHIERARCHICAL
D4V1, survival
          sevent
clus2       0  1
  subtype1 22 14
  subtype2 36 17
  subtype3  9  3
subtype1 subtype2 subtype3 
      36       53       12 
subtype1 subtype2 subtype3 
      14       17        3 
$subtype1
TCGA-IG-A4QS TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH 
        0.26         0.99        14.86       122.10        60.39        42.77 
TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43M TCGA-L5-A4OF TCGA-L5-A4OH TCGA-L5-A4OI 
        3.16         3.45         8.94         3.68        19.50         8.78 
TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR 
        6.41        18.35         3.32         7.17         1.38         3.16 
TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A891 
       30.74         4.90        29.00         7.13         7.43         3.95 
TCGA-L5-A8NJ TCGA-L5-A8NU TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6DQ 
       16.47        83.24        10.36        17.62         8.02         7.59 
TCGA-R6-A6KZ TCGA-R6-A6XG TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RE 
        5.06        29.59         9.30         7.00         8.78         4.80 

$subtype2
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC 
       33.27        20.09         0.85        20.78         2.63        20.12 
TCGA-IG-A4P3 TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 
        0.03         0.53        17.03         0.79        23.41         0.36 
TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG 
        0.13         0.46        44.75        68.02         3.68        41.52 
TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88S TCGA-L5-A88W 
        6.21         0.30         4.31         4.08         6.94        25.12 
TCGA-L5-A88Z TCGA-L5-A8NQ TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N 
        7.40        21.37         0.07        10.45         0.16         0.07 
TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A49W 
        0.33         0.10         0.13         0.07         0.10         0.07 
TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A5 
        0.10         0.07         0.13         0.07         0.10         0.10 
TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 
        0.10         0.07         0.07         0.10         0.07         0.20 
TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-VR-A8EU TCGA-VR-A8EW 
        1.18         5.16        14.01        18.31         8.12 

$subtype3
TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A88T TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A893 
        3.52         3.35         8.71         2.60         0.36         3.02 
TCGA-Q9-A6FW TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-V5-A7RB 
        3.78        14.70         7.04         6.35        53.95         5.29 

subtype1 subtype2 subtype3 
    0.26     0.03     0.36 
subtype1 subtype2 subtype3 
  122.10    68.02    53.95 
subtype1 subtype2 subtype3 
   7.805    0.530    4.535 
[1] "0.3 - 122.1 (7.8)" "0.0 - 68.0 (0.5)"  "0.4 - 54.0 (4.5)" 
D4V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       5        2        1        0         4         7         1
  subtype2       0        2        3        1        26         9         9
  subtype3       2        0        0        0         0         1         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1          3          1          3        1
  subtype2          5          4          0        1
  subtype3          0          2          0        0
D4V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           5        0        2
  STAGE IA          2        2        0
  STAGE IB          1        3        0
  STAGE II          0        1        0
  STAGE IIA         4       26        0
  STAGE IIB         7        9        1
  STAGE III         1        9        1
  STAGE IIIA        3        5        0
  STAGE IIIB        1        4        2
  STAGE IIIC        3        0        0
  STAGE IV          1        1        0
[1] 11  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       T0+T1 T2 T3 T4
  subtype1    11  6 12  1
  subtype2     5 19 34  2
  subtype3     4  1  3  0
D4V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       11        5        4
  T2           6       19        1
  T3          12       34        3
  T4           1        2        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       N0 N1 N2 N3
  subtype1 12 11  3  3
  subtype2 36 20  4  0
  subtype3  3  3  2  0
D4V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       12       36        3
  N1       11       20        3
  N2        3        4        2
  N3        3        0        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       M0 M1 M1A MX
  subtype1 19  0   1  8
  subtype2 54  1   0  4
  subtype3  4  0   0  3
D4V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        19       54        4
  M1         0        1        0
  M1A        1        0        0
  MX         8        4        3
[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"
D4V7, binary
          cls
clus        0  1
  subtype1  8 28
  subtype2  6 54
  subtype3  2 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    8   28
  subtype2    6   54
  subtype3    2   10
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        8        6        2
  MALE         28       54       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"
D4V8, continuous
          vv
clus       ASIAN WHITE
  subtype1     0    33
  subtype2    36    24
  subtype3     0    11
D4V9, multiclass
       clus
vv      subtype1 subtype2 subtype3
  ASIAN        0       36        0
  WHITE       33       24       11
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(5) Variable = MIRSEQ_CNMF
D5V1, survival
          sevent
clus2       0  1
  subtype1 43 33
  subtype2 36 20
  subtype3  8  2
subtype1 subtype2 subtype3 
      76       56       10 
subtype1 subtype2 subtype3 
      33       20        2 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GR TCGA-IG-A4QS 
        5.92        13.94         8.94        16.24        32.45         0.26 
TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A939 TCGA-JY-A93C 
      122.10        60.39        42.77        25.41        15.48        23.18 
TCGA-JY-A93D TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OF 
       25.28         3.16         3.45         8.94         3.52         3.68 
TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO 
        3.35        19.50         8.78         6.41        18.35         3.32 
TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU 
        7.17         1.38         3.16        30.74         4.90        29.00 
TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A893 
        7.13         7.43         2.60         0.36         3.95         3.02 
TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NG TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ 
       55.50         2.66        35.97        12.92        13.48        16.47 
TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NT 
       13.22         7.76         5.42         8.71        13.41        27.12 
TCGA-L5-A8NU TCGA-L5-A8NV TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-Q9-A6FW 
       83.24        52.57        46.09        10.36        17.62         3.78 
TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG 
        8.02         7.59         5.06        14.70         7.04        29.59 
TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB 
        6.35        53.95         9.30         7.00         8.78         5.29 
TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX TCGA-ZR-A9CJ 
        4.80         8.15         4.44        18.12 

$subtype2
TCGA-2H-A9GQ TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YC TCGA-IG-A4P3 
        4.21        33.27        20.09         0.85        20.12         0.03 
TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS 
        0.53        17.03         0.79        23.41         0.36         0.13 
TCGA-IG-A8O2 TCGA-IG-A97H TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG 
        0.46         0.43        44.75        68.02         3.68        41.52 
TCGA-JY-A93F TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK 
       17.59         4.31         4.08        25.12         7.40        13.55 
TCGA-L5-A8NQ TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49O TCGA-LN-A49R 
       21.37         0.07        10.45         0.16         0.33         0.10 
TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A2 
        0.13         0.07         0.07         0.10         0.07         0.13 
TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
        0.07         0.10         0.10         0.10         0.07         0.07 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW 
        0.10         0.07         0.20         1.18         5.16        14.01 
TCGA-V5-A7RC TCGA-V5-AASV TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8Q7 TCGA-VR-AA4G 
        3.42         8.48        18.31         8.12        36.72        12.03 
TCGA-VR-AA7D TCGA-VR-AA7I 
        9.17        15.91 

$subtype3
TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A93E TCGA-KH-A6WC 
       20.78         2.63         0.99        14.86        18.08         6.21 
TCGA-L5-A43H TCGA-L5-A88S TCGA-L5-A88T TCGA-LN-A49N 
        0.30         6.94         8.71         0.07 

subtype1 subtype2 subtype3 
    0.26     0.03     0.07 
subtype1 subtype2 subtype3 
  122.10    68.02    20.78 
subtype1 subtype2 subtype3 
   8.940    2.300    6.575 
[1] "0.3 - 122.1 (8.9)" "0.0 - 68.0 (2.3)"  "0.1 - 20.8 (6.6)" 
D5V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       8        2        2        0         5        15        13
  subtype2       0        1        3        1        27         9        10
  subtype3       0        1        1        0         2         2         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          4          5        2         2
  subtype2          5          4          1        1         0
  subtype3          4          0          0        0         0
D5V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           8        0        0
  STAGE IA          2        1        1
  STAGE IB          2        3        1
  STAGE II          0        1        0
  STAGE IIA         5       27        2
  STAGE IIB        15        9        2
  STAGE III        13       10        1
  STAGE IIIA        2        5        4
  STAGE IIIB        4        4        0
  STAGE IIIC        5        1        0
  STAGE IV          2        1        0
  STAGE IVA         2        0        0
[1] 12  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       T0+T1 T2 T3 T4
  subtype1    21 10 33  0
  subtype2     4 21 35  2
  subtype3     1  2  6  2
D5V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       21        4        1
  T2          10       21        2
  T3          33       35        6
  T4           0        2        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       N0 N1 N2 N3
  subtype1 22 31  6  5
  subtype2 36 19  5  1
  subtype3  5  5  0  0
D5V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       22       36        5
  N1       31       19        5
  N2        6        5        0
  N3        5        1        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       M0 M1 M1A MX
  subtype1 46  1   3 11
  subtype2 56  1   0  4
  subtype3  9  0   0  2
D5V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        46       56        9
  M1         1        1        0
  M1A        3        0        0
  MX        11        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"
D5V7, binary
          cls
clus        0  1
  subtype1 11 65
  subtype2  9 54
  subtype3  1 10
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   65
  subtype2    9   54
  subtype3    1   10
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       11        9        1
  MALE         65       54       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"
D5V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    59
  subtype2    34                         2    25
  subtype3     2                         0     9
D5V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1       34        2
  BLACK OR AFRICAN AMERICAN        0        2        0
  WHITE                           59       25        9
[1] 3 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(6) Variable = MIRSEQ_CHIERARCHICAL
D6V1, survival
          sevent
clus2       0  1
  subtype1 28 28
  subtype2 18  6
  subtype3 25 16
  subtype4 16  5
subtype1 subtype2 subtype3 subtype4 
      56       24       41       21 
subtype1 subtype2 subtype3 subtype4 
      28        6       16        5 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK TCGA-2H-A9GL 
       25.78        20.05        14.30        58.55         7.63         5.92 
TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GQ TCGA-IG-A4QS TCGA-JY-A6F8 
       13.94         8.94        16.24         4.21         0.26       122.10 
TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43E TCGA-L5-A4OE TCGA-L5-A4OF 
       60.39        42.77        23.18         3.45         3.52         3.68 
TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OP 
        3.35        19.50         8.78         6.41        18.35         7.17 
TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V 
        1.38         3.16        30.74         7.13         7.43         2.60 
TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH TCGA-L5-A8NI 
        0.36         3.95        55.50         2.66        12.92        13.48 
TCGA-L5-A8NJ TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 
       16.47         7.76         5.42        46.09        10.36        17.62 
TCGA-R6-A6DN TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG TCGA-R6-A6XQ 
        8.02         5.06        14.70         7.04        29.59         6.35 
TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW 
       53.95         9.30         7.00         5.29         4.80         8.15 
TCGA-V5-AASX TCGA-ZR-A9CJ 
        4.44        18.12 

$subtype2
TCGA-2H-A9GH TCGA-2H-A9GR TCGA-IG-A7DP TCGA-JY-A938 TCGA-JY-A939 TCGA-JY-A93D 
       31.27        32.45        14.86        25.41        15.48        25.28 
TCGA-JY-A93E TCGA-L5-A43C TCGA-L5-A43M TCGA-L5-A4OO TCGA-L5-A4OT TCGA-L5-A4OU 
       18.08         3.16         8.94         3.32         4.90        29.00 
TCGA-L5-A88T TCGA-L5-A893 TCGA-L5-A8NG TCGA-L5-A8NL TCGA-L5-A8NR TCGA-L5-A8NS 
        8.71         3.02        35.97        13.22         8.71        13.41 
TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L5-A8NV TCGA-Q9-A6FW TCGA-R6-A6DQ TCGA-S8-A6BV 
       27.12        83.24        52.57         3.78         7.59         8.78 

$subtype3
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4P3 
       33.27        20.09         0.85        20.78         2.63         0.03 
TCGA-IG-A4QT TCGA-IG-A50L TCGA-IG-A5S3 TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A97H 
        0.99         0.53        23.41         0.36         0.13         0.43 
TCGA-JY-A6FE TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A88S TCGA-L5-A88Z 
        3.68         6.21         0.30         4.31         6.94         7.40 
TCGA-L5-A8NQ TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R 
       21.37         0.07        10.45         0.07         0.33         0.10 
TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 
        0.07         0.10         0.13         0.10         0.10         0.10 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-A7RC 
        0.10         0.07         0.20         5.16        14.01         3.42 
TCGA-V5-AASV TCGA-VR-A8EW TCGA-VR-AA4G TCGA-VR-AA7D TCGA-VR-AA7I 
        8.48         8.12        12.03         9.17        15.91 

$subtype4
TCGA-IG-A3YC TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-JY-A6FD 
       20.12        17.03         0.79         0.46        44.75        68.02 
TCGA-JY-A6FG TCGA-JY-A93F TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A8NK TCGA-LN-A49M 
       41.52        17.59         4.08        25.12        13.55         0.16 
TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49Y TCGA-LN-A4A3 TCGA-LN-A4A8 TCGA-LN-A4A9 
        0.13         0.07         0.07         0.07         0.07         0.07 
TCGA-LN-A5U7 TCGA-VR-A8EU TCGA-VR-A8Q7 
        1.18        18.31        36.72 

subtype1 subtype2 subtype3 subtype4 
    0.26     3.02     0.03     0.07 
subtype1 subtype2 subtype3 subtype4 
  122.10    83.24    33.27    68.02 
subtype1 subtype2 subtype3 subtype4 
   8.085   14.135    0.990    4.080 
[1] "0.3 - 122.1 (8.1)" "3.0 - 83.2 (14.1)" "0.0 - 33.3 (1.0)" 
[4] "0.1 - 68.0 (4.1)" 
D6V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        2        0         1        10        11
  subtype2       1        0        0        0         4         6         3
  subtype3       0        1        2        1        16         8         8
  subtype4       0        1        2        0        13         2         2
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          1          3          3        1         2
  subtype2          3          1          2        1         0
  subtype3          5          3          1        0         0
  subtype4          2          1          0        1         0
D6V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           7        1        0        0
  STAGE IA          2        0        1        1
  STAGE IB          2        0        2        2
  STAGE II          0        0        1        0
  STAGE IIA         1        4       16       13
  STAGE IIB        10        6        8        2
  STAGE III        11        3        8        2
  STAGE IIIA        1        3        5        2
  STAGE IIIB        3        1        3        1
  STAGE IIIC        3        2        1        0
  STAGE IV          1        1        0        1
  STAGE IVA         2        0        0        0
[1] 12  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       T0+T1 T2 T3 T4
  subtype1    18  8 20  0
  subtype2     3  3 15  1
  subtype3     2 13 27  3
  subtype4     3  9 12  0
D6V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1       18        3        2        3
  T2           8        3       13        9
  T3          20       15       27       12
  T4           0        1        3        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       N0 N1 N2 N3
  subtype1 14 25  4  3
  subtype2  8  9  2  2
  subtype3 25 14  4  1
  subtype4 16  7  1  0
D6V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       14        8       25       16
  N1       25        9       14        7
  N2        4        2        4        1
  N3        3        2        1        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       M0 M1 M1A MX
  subtype1 31  1   2  9
  subtype2 18  0   1  3
  subtype3 41  0   0  4
  subtype4 21  1   0  1
D6V6, multiclass
     clus
vv    subtype1 subtype2 subtype3 subtype4
  M0        31       18       41       21
  M1         1        0        0        1
  M1A        2        1        0        0
  MX         9        3        4        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"
D6V7, binary
          cls
clus        0  1
  subtype1  7 49
  subtype2  5 19
  subtype3  5 41
  subtype4  4 20
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7   49
  subtype2    5   19
  subtype3    5   41
  subtype4    4   20
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        7        5        5        4
  MALE         49       19       41       20
[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"
D6V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    42
  subtype2     0                         0    20
  subtype3    22                         2    21
  subtype4    14                         0    10
D6V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            1        0       22       14
  BLACK OR AFRICAN AMERICAN        0        0        2        0
  WHITE                           42       20       21       10
[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(7) Variable = MIRSEQ_MATURE_CNMF
D7V1, survival
          sevent
clus2       0  1
  subtype1 32 28
  subtype2 24 17
  subtype3 23  7
  subtype4  4  3
subtype1 subtype2 subtype3 subtype4 
      60       41       30        7 
subtype1 subtype2 subtype3 subtype4 
      28       17        7        3 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-IG-A4QS TCGA-JY-A6F8 
        5.92        13.94         8.94        16.24         0.26       122.10 
TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-JY-A93C TCGA-L5-A43C TCGA-L5-A43E 
       60.39        42.77        25.41        23.18         3.16         3.45 
TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4ON 
        8.94         3.52         3.35        19.50         8.78        18.35 
TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU 
        7.17         1.38         3.16        30.74         4.90        29.00 
TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A893 
        7.13         7.43         2.60         0.36         3.95         3.02 
TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NM 
       55.50         2.66        12.92        13.48        16.47         7.76 
TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6DN 
        5.42         8.71        46.09        10.36        17.62         8.02 
TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 
        7.59         5.06        14.70        29.59         6.35        53.95 
TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASW TCGA-V5-AASX 
        7.00         8.78         5.29         4.80         8.15         4.44 

$subtype2
TCGA-2H-A9GQ TCGA-IG-A3QL TCGA-IG-A4P3 TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 
        4.21        20.09         0.03        17.03         0.79        23.41 
TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97H TCGA-JY-A6FA TCGA-JY-A6FE 
        0.36         0.13         0.46         0.43        44.75         3.68 
TCGA-JY-A6FG TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A88Z TCGA-LN-A49K 
       41.52         4.31         4.08        25.12         7.40         0.07 
TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U 
       10.45         0.16         0.33         0.10         0.13         0.07 
TCGA-LN-A49Y TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
        0.07         0.13         0.10         0.10         0.07         0.07 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW 
        0.10         0.07         0.20         1.18         5.16        14.01 
TCGA-V5-A7RC TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8Q7 TCGA-VR-AA7D 
        3.42        18.31         8.12        36.72         9.17 

$subtype3
TCGA-2H-A9GR TCGA-IG-A3I8 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC TCGA-IG-A4QT 
       32.45        33.27        20.78         2.63        20.12         0.99 
TCGA-IG-A50L TCGA-IG-A7DP TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E TCGA-KH-A6WC 
        0.53        14.86        15.48        25.28        18.08         6.21 
TCGA-L5-A43H TCGA-L5-A4OF TCGA-L5-A4OO TCGA-L5-A88S TCGA-L5-A88T TCGA-L5-A8NG 
        0.30         3.68         3.32         6.94         8.71        35.97 
TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L5-A8NV 
       13.55        21.37        13.41        27.12        83.24        52.57 
TCGA-LN-A49N TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A4A5 TCGA-Q9-A6FW TCGA-VR-AA7I 
        0.07         0.07         0.10         0.10         3.78        15.91 

$subtype4
TCGA-IG-A3Y9 TCGA-JY-A6FD TCGA-L5-A8NL TCGA-R6-A6L6 TCGA-R6-A6Y2 TCGA-VR-AA4G 
        0.85        68.02        13.22         7.04         9.30        12.03 
TCGA-ZR-A9CJ 
       18.12 

subtype1 subtype2 subtype3 subtype4 
    0.26     0.03     0.07     0.85 
subtype1 subtype2 subtype3 subtype4 
  122.10    44.75    83.24    68.02 
subtype1 subtype2 subtype3 subtype4 
   8.745    0.790   13.480   12.030 
[1] "0.3 - 122.1 (8.7)" "0.0 - 44.8 (0.8)"  "0.1 - 83.2 (13.5)"
[4] "0.8 - 68.0 (12.0)"
D7V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        2        0         2        11        11
  subtype2       0        1        2        1        20         8         7
  subtype3       0        1        1        0        11         6         4
  subtype4       0        0        0        0         1         0         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          3          2        2         2
  subtype2          1          4          1        1         0
  subtype3          6          1          2        0         0
  subtype4          2          0          1        0         0
D7V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           7        0        0        0
  STAGE IA          2        1        1        0
  STAGE IB          2        2        1        0
  STAGE II          0        1        0        0
  STAGE IIA         2       20       11        1
  STAGE IIB        11        8        6        0
  STAGE III        11        7        4        1
  STAGE IIIA        2        1        6        2
  STAGE IIIB        3        4        1        0
  STAGE IIIC        2        1        2        1
  STAGE IV          2        1        0        0
  STAGE IVA         2        0        0        0
[1] 12  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       T0+T1 T2 T3 T4
  subtype1    18  8 24  0
  subtype2     4 16 26  0
  subtype3     3  7 19  3
  subtype4     0  1  3  1
D7V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1       18        4        3        0
  T2           8       16        7        1
  T3          24       26       19        3
  T4           0        0        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       N0 N1 N2 N3
  subtype1 16 27  5  2
  subtype2 25 15  4  1
  subtype3 17 11  1  2
  subtype4  2  1  1  1
D7V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       16       25       17        2
  N1       27       15       11        1
  N2        5        4        1        1
  N3        2        1        2        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       M0 M1 M1A MX
  subtype1 34  1   3 10
  subtype2 41  1   0  3
  subtype3 29  0   0  2
  subtype4  4  0   0  1
D7V6, multiclass
     clus
vv    subtype1 subtype2 subtype3 subtype4
  M0        34       41       29        4
  M1         1        1        0        0
  M1A        3        0        0        0
  MX        10        3        2        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"
D7V7, binary
          cls
clus        0  1
  subtype1 10 50
  subtype2  4 43
  subtype3  3 29
  subtype4  2  5
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   10   50
  subtype2    4   43
  subtype3    3   29
  subtype4    2    5
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE       10        4        3        2
  MALE         50       43       29        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"
D7V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    44
  subtype2    28                         1    16
  subtype3     6                         0    25
  subtype4     1                         0     6
D7V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            1       28        6        1
  BLACK OR AFRICAN AMERICAN        0        1        0        0
  WHITE                           44       16       25        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(8) Variable = MIRSEQ_MATURE_CHIERARCHICAL
D8V1, survival
          sevent
clus2       0  1
  subtype1 28 29
  subtype2 15  5
  subtype3 40 21
subtype1 subtype2 subtype3 
      57       20       61 
subtype1 subtype2 subtype3 
      29        5       21 
$subtype1
TCGA-2H-A9GF TCGA-2H-A9GG TCGA-2H-A9GH TCGA-2H-A9GI TCGA-2H-A9GJ TCGA-2H-A9GK 
       25.78        20.05        31.27        14.30        58.55         7.63 
TCGA-2H-A9GL TCGA-2H-A9GM TCGA-2H-A9GN TCGA-2H-A9GO TCGA-2H-A9GQ TCGA-IG-A4QS 
        5.92        13.94         8.94        16.24         4.21         0.26 
TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A93C TCGA-L5-A43E TCGA-L5-A4OE 
      122.10        60.39        42.77        23.18         3.45         3.52 
TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4ON TCGA-L5-A4OP 
        3.68         3.35        19.50         8.78        18.35         7.17 
TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V 
        1.38         3.16        30.74         7.13         7.43         2.60 
TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH TCGA-L5-A8NI 
        0.36         3.95        55.50         2.66        12.92        13.48 
TCGA-L5-A8NJ TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NW TCGA-L7-A6VZ 
       16.47         7.76         5.42         8.71        46.09        10.36 
TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG 
       17.62         8.02         5.06        14.70         7.04        29.59 
TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-A7RE 
        6.35        53.95         9.30         7.00         5.29         4.80 
TCGA-V5-AASW TCGA-V5-AASX TCGA-ZR-A9CJ 
        8.15         4.44        18.12 

$subtype2
TCGA-2H-A9GR TCGA-JY-A938 TCGA-JY-A939 TCGA-JY-A93D TCGA-JY-A93E TCGA-L5-A43C 
       32.45        25.41        15.48        25.28        18.08         3.16 
TCGA-L5-A43M TCGA-L5-A4OO TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A893 TCGA-L5-A8NG 
        8.94         3.32         4.90        29.00         3.02        35.97 
TCGA-L5-A8NL TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L5-A8NV TCGA-Q9-A6FW 
       13.22        13.41        27.12        83.24        52.57         3.78 
TCGA-R6-A6DQ TCGA-S8-A6BV 
        7.59         8.78 

$subtype3
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A3YC 
       33.27        20.09         0.85        20.78         2.63        20.12 
TCGA-IG-A4P3 TCGA-IG-A4QT TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A5S3 
        0.03         0.99         0.53        17.03         0.79        23.41 
TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A7DP TCGA-IG-A8O2 TCGA-IG-A97H TCGA-JY-A6FA 
        0.36         0.13        14.86         0.46         0.43        44.75 
TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A43J 
       68.02         3.68        41.52         6.21         0.30         4.31 
TCGA-L5-A4OM TCGA-L5-A88S TCGA-L5-A88T TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK 
        4.08         6.94         8.71        25.12         7.40        13.55 
TCGA-L5-A8NQ TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O 
       21.37         0.07        10.45         0.16         0.07         0.33 
TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y 
        0.10         0.13         0.07         0.07         0.10         0.07 
TCGA-LN-A4A2 TCGA-LN-A4A4 TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
        0.13         0.10         0.10         0.10         0.07         0.07 
TCGA-LN-A4MQ TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW 
        0.10         0.07         0.20         1.18         5.16        14.01 
TCGA-V5-A7RC TCGA-VR-A8EU TCGA-VR-A8EW TCGA-VR-A8Q7 TCGA-VR-AA4G TCGA-VR-AA7D 
        3.42        18.31         8.12        36.72        12.03         9.17 
TCGA-VR-AA7I 
       15.91 

subtype1 subtype2 subtype3 
    0.26     3.02     0.03 
subtype1 subtype2 subtype3 
  122.10    83.24    68.02 
subtype1 subtype2 subtype3 
   8.710   14.445    2.630 
[1] "0.3 - 122.1 (8.7)" "3.0 - 83.2 (14.4)" "0.0 - 68.0 (2.6)" 
D8V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       6        2        2        0         1        11        12
  subtype2       1        0        0        0         4         4         2
  subtype3       0        2        3        1        29        10         9
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          1          3          3        1         2
  subtype2          2          1          2        1         0
  subtype3          8          4          1        1         0
D8V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           6        1        0
  STAGE IA          2        0        2
  STAGE IB          2        0        3
  STAGE II          0        0        1
  STAGE IIA         1        4       29
  STAGE IIB        11        4       10
  STAGE III        12        2        9
  STAGE IIIA        1        2        8
  STAGE IIIB        3        1        4
  STAGE IIIC        3        2        1
  STAGE IV          1        1        1
  STAGE IVA         2        0        0
[1] 12  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       T0+T1 T2 T3 T4
  subtype1    18  8 21  0
  subtype2     2  2 14  0
  subtype3     5 22 37  4
D8V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       18        2        5
  T2           8        2       22
  T3          21       14       37
  T4           0        0        4
[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       N0 N1 N2 N3
  subtype1 13 27  4  3
  subtype2  8  6  2  2
  subtype3 39 21  5  1
D8V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       13        8       39
  N1       27        6       21
  N2        4        2        5
  N3        3        2        1
[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       M0 M1 M1A MX
  subtype1 32  1   2  9
  subtype2 15  0   1  2
  subtype3 61  1   0  5
D8V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        32       15       61
  M1         1        0        1
  M1A        2        1        0
  MX         9        2        5
[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"
D8V7, binary
          cls
clus        0  1
  subtype1  7 50
  subtype2  3 17
  subtype3  9 60
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    7   50
  subtype2    3   17
  subtype3    9   60
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        7        3        9
  MALE         50       17       60
[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"
D8V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     1                         0    41
  subtype2     0                         0    18
  subtype3    35                         1    32
D8V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            1        0       35
  BLACK OR AFRICAN AMERICAN        0        0        1
  WHITE                           41       18       32
[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"
