[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/10005875/ESCA-TP.merged_data.txt"
[1] "dfn:"
[1] "/xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/ESCA-TP/10668123/ESCA-TP.mergedcluster.txt"

nPatients in clinical file=127, in cluster file=185, common to both=127
[1]   8 127
[1] "CN_CNMF"
[1] 3
 1  2  3 
37 36 32 
 1  2  3 
37 36 32 
[1] "METHLYATION_CNMF"
[1] 3
 1  2  3 
55 24 48 
 1  2  3 
55 24 48 
[1] "MRNASEQ_CNMF"
[1] 3
 1  2  3  4 
13 23  6 24 
 1  2  3  4 
13 23  6 24 
[1] "MRNASEQ_CHIERARCHICAL"
[1] 3
 1  2  3  4 
12 20 26  8 
 1  2  3  4 
12 20 26  8 
[1] "MIRSEQ_CNMF"
[1] 3
 1  2  3 
60 54 10 
 1  2  3 
60 54 10 
[1] "MIRSEQ_CHIERARCHICAL"
[1] 3
 1  2  3  4 
44 20 35 25 
 1  2  3  4 
44 20 35 25 
[1] "MIRSEQ_MATURE_CNMF"
[1] 3
 1  2  3 
56 50 18 
 1  2  3 
56 50 18 
[1] "MIRSEQ_MATURE_CHIERARCHICAL"
[1] 3
 1  2  3 
48 15 61 
 1  2  3 
48 15 61 
[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 127 columns.

[1] "Batch" "15"   
[1] "Last Follow UP"
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-A625 TCGA-IG-A6QS TCGA-IG-A7DP TCGA-IG-A8O2 TCGA-IG-A97H TCGA-IG-A97I 
          11            4           34           14           13           NA 
TCGA-JY-A6F8 TCGA-JY-A6FA TCGA-JY-A6FB TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG 
        3714           NA         1837         1638           NA           NA 
TCGA-JY-A6FH TCGA-JY-A938 TCGA-KH-A6WC TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43H 
        1301          773          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-ZR-A9CJ 
         551 
Variable 1:'AGE':	nDistinctValues=44,	numeric=TRUE,	binary=FALSE,	exclude=FALSE.
Variable 2:'VITALSTATUS':	nDistinctValues=2,	numeric=TRUE,	binary=TRUE,	exclude=FALSE.
Variable 3:'DAYSTODEATH':	nDistinctValues=37,	numeric=TRUE,	binary=FALSE,	exclude=TRUE.
Variable 4:'DAYSTOLASTFOLLOWUP':	nDistinctValues=70,	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=1,	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=37,	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 127 columns, 1 survival variables, and 8 non-survival variables.
AGE, nv=44, 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 20 30 60  3 
[1] "table(vv)"
vv
T0+T1    T2 T3+T4 
   21    30    63 
$ClinVariableName
[1] "PATHOLOGY.T.STAGE"

$Table
vv
T0 T1 T2 T3 T4 
 1 20 30 60  3 

$nClasses
[1] 3

$ClinVariableType
[1] "multiclass(3)"


T0+T1    T2 T3+T4 
   21    30    63 
PATHOLOGY.N.STAGE, nv=4, binary=FALSE, numeric=TRUE
[1] "grepl('PATHOLOGY.N',vnm)"
vv
N0 N1 N2 N3 
59 41  8  4 
[1] "table(vv)"
vv
N0 N1 N2 N3 
59 41  8  4 
$ClinVariableName
[1] "PATHOLOGY.N.STAGE"

$Table
vv
N0 N1 N2 N3 
59 41  8  4 

$nClasses
[1] 4

$ClinVariableType
[1] "multiclass(4)"


N0 N1 N2 N3 
59 41  8  4 
PATHOLOGY.M.STAGE, nv=4, binary=FALSE, numeric=FALSE
GENDER, nv=2, binary=FALSE, numeric=FALSE
NUMBERPACKYEARSSMOKED, nv=37, binary=FALSE, numeric=TRUE
RACE, nv=3, binary=FALSE, numeric=FALSE

Clustering(1) Variable = CN_CNMF
D1V1, survival
          sevent
clus2       0  1
  subtype1 23 12
  subtype2 26  6
  subtype3 18 13
subtype1 subtype2 subtype3 
      35       32       31 
subtype1 subtype2 subtype3 
      12        6       13 
$subtype1
TCGA-IG-A3Y9 TCGA-IG-A3YB TCGA-IG-A3YC TCGA-IG-A4QT TCGA-IG-A5B8 TCGA-IG-A7DP 
        0.85         2.63        20.12         0.99         0.79         1.12 
TCGA-JY-A6F8 TCGA-JY-A6FD TCGA-JY-A6FG TCGA-KH-A6WC TCGA-L5-A43C TCGA-L5-A43M 
      122.10        53.85        41.52         6.21         3.16         8.94 
TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4OO TCGA-L5-A4OP 
        3.68         3.35         8.78         6.41         3.32         7.17 
TCGA-L5-A4OS TCGA-L5-A4OU TCGA-L5-A88T TCGA-L5-A88W TCGA-L5-A893 TCGA-L5-A8NQ 
       30.74        29.00         8.71        25.12         3.02        21.37 
TCGA-L5-A8NU TCGA-LN-A49X TCGA-LN-A4A5 TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6L6 
       83.24         0.10         0.10        17.62         3.78         7.04 
TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-V5-A7RB 
       29.59         6.35         9.30         7.00         5.29 

$subtype2
TCGA-IG-A3I8 TCGA-IG-A3YA TCGA-IG-A4P3 TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A6QS 
       33.27        20.78         0.03         0.53        17.03         0.13 
TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88S 
        0.46        44.75         0.30         4.31         4.08         6.94 
TCGA-L5-A88Z TCGA-LN-A49K TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R 
        7.40         0.07         0.16         0.07         0.33         0.10 
TCGA-LN-A49S TCGA-LN-A49W TCGA-LN-A49Y TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 
        0.13         0.07         0.07         0.13         0.07         0.10 
TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 
        0.10         0.07         0.07         0.07         0.20         1.18 
TCGA-Q9-A6FU TCGA-S8-A6BW 
        5.16        14.01 

$subtype3
TCGA-IG-A3QL TCGA-IG-A4QS TCGA-IG-A625 TCGA-JY-A6FB TCGA-JY-A6FE TCGA-JY-A6FH 
       20.09         0.26         0.36        60.39         3.68        42.77 
TCGA-L5-A43E TCGA-L5-A4OE TCGA-L5-A4OH TCGA-L5-A4ON TCGA-L5-A4OQ TCGA-L5-A4OR 
        3.45         3.52        19.50        18.35         1.38         3.16 
TCGA-L5-A4OT TCGA-L5-A4OW TCGA-L5-A4OX TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 
        4.90         7.13         7.43         2.60         0.36         3.95 
TCGA-L5-A8NJ TCGA-L7-A6VZ TCGA-LN-A49L TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A4MQ 
       16.47        10.36        10.45         0.07         0.10         0.10 
TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6Y0 TCGA-S8-A6BV 
        8.02         7.59         5.06        14.70        53.95         8.78 
TCGA-V5-A7RE 
        4.80 

subtype1 subtype2 subtype3 
    0.10     0.03     0.07 
subtype1 subtype2 subtype3 
  122.10    44.75    60.39 
subtype1 subtype2 subtype3 
    7.00     0.18     5.06 
[1] "0.1 - 122.1 (7.0)" "0.0 - 44.8 (0.2)"  "0.1 - 60.4 (5.1)" 
D1V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       4        2        1        0        10         4         2
  subtype2       0        1        2        1        16         7         5
  subtype3       3        1        1        0         4         5         4
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1          4          1          2        0
  subtype2          2          2          0        0
  subtype3          2          3          1        1
D1V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           4        0        3
  STAGE IA          2        1        1
  STAGE IB          1        2        1
  STAGE II          0        1        0
  STAGE IIA        10       16        4
  STAGE IIB         4        7        5
  STAGE III         2        5        4
  STAGE IIIA        4        2        2
  STAGE IIIB        1        2        3
  STAGE IIIC        2        0        1
  STAGE IV          0        0        1
[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     9  5    18
  subtype2     3 15    18
  subtype3     7  6    14
D1V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1        9        3        7
  T2           5       15        6
  T3+T4       18       18       14
[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"
          vv
clus       N0 N1 N2 N3
  subtype1 18  9  2  2
  subtype2 21 13  2  0
  subtype3 11 11  4  1
D1V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       18       21       11
  N1        9       13       11
  N2        2        2        4
  N3        2        0        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 M1A MX
  subtype1 25   0  6
  subtype2 32   0  3
  subtype3 18   1  6
D1V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        25       32       18
  M1A        0        0        1
  MX         6        3        6
[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"
D1V7, binary
          cls
clus        0  1
  subtype1  9 28
  subtype2  4 32
  subtype3  2 30
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   28
  subtype2    4   32
  subtype3    2   30
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        9        4        2
  MALE         28       32       30
[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 WHITE
  subtype1     5    29
  subtype2    24    12
  subtype3     6    25
D1V9, multiclass
       clus
vv      subtype1 subtype2 subtype3
  ASIAN        5       24        6
  WHITE       29       12       25
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(2) Variable = METHLYATION_CNMF
D2V1, survival
          sevent
clus2       0  1
  subtype1 36 19
  subtype2 15  7
  subtype3 30 12
subtype1 subtype2 subtype3 
      55       22       42 
subtype1 subtype2 subtype3 
      19        7       12 
$subtype1
TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-L5-A43C 
        0.26       122.10        60.39        42.77        25.41         3.16 
TCGA-L5-A43E TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI 
        3.45         3.52         3.68         3.35        19.50         8.78 
TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OR TCGA-L5-A4OT TCGA-L5-A4OU 
        6.41        18.35         7.17         3.16         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-A8NV TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DN 
       52.57        46.09        10.36        17.62         3.78         8.02 
TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y2 
        7.59         5.06        14.70        29.59         6.35         9.30 
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 
TCGA-ZR-A9CJ 
       18.12 

$subtype2
TCGA-IG-A3YA TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A4QT TCGA-IG-A5B8 TCGA-IG-A7DP 
       20.78        20.12         0.03         0.99         0.79         1.12 
TCGA-IG-A97H TCGA-KH-A6WC TCGA-L5-A43M TCGA-L5-A4OO TCGA-L5-A4OQ TCGA-L5-A4OS 
        0.43         6.21         8.94         3.32         1.38        30.74 
TCGA-L5-A88S TCGA-L5-A88T TCGA-L5-A8NQ TCGA-L5-A8NU TCGA-LN-A49W TCGA-LN-A49X 
        6.94         8.71        21.37        83.24         0.07         0.10 
TCGA-LN-A4A3 TCGA-LN-A4A5 TCGA-R6-A6L6 TCGA-R6-A6Y0 
        0.07         0.10         7.04        53.95 

$subtype3
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YB TCGA-IG-A50L TCGA-IG-A51D 
       33.27        20.09         0.85         2.63         0.53        17.03 
TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE 
        0.36         0.13         0.46        44.75        53.85         3.68 
TCGA-JY-A6FG TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A88Z 
       41.52         0.30         4.31         4.08        25.12         7.40 
TCGA-L5-A8NK TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O 
       13.55         0.07        10.45         0.16         0.07         0.33 
TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49V TCGA-LN-A49Y TCGA-LN-A4A2 
        0.10         0.13         0.07         0.10         0.07         0.13 
TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR 
        0.10         0.10         0.07         0.07         0.10         0.07 
TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-A7RC TCGA-V5-AASV 
        0.20         1.18         5.16        14.01         3.42         8.48 

subtype1 subtype2 subtype3 
    0.26     0.03     0.07 
subtype1 subtype2 subtype3 
  122.10    83.24    53.85 
subtype1 subtype2 subtype3 
   8.020    4.765    0.495 
[1] "0.3 - 122.1 (8.0)" "0.0 - 83.2 (4.8)"  "0.1 - 53.9 (0.5)" 
D2V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        2        0         3        11         7
  subtype2       0        1        2        0         7         3         3
  subtype3       0        1        1        1        24         8         6
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          1          3          3        2         1
  subtype2          4          0          1        0         0
  subtype3          3          3          0        0         0
D2V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           7        0        0
  STAGE IA          2        1        1
  STAGE IB          2        2        1
  STAGE II          0        0        1
  STAGE IIA         3        7       24
  STAGE IIB        11        3        8
  STAGE III         7        3        6
  STAGE IIIA        1        4        3
  STAGE IIIB        3        0        3
  STAGE IIIC        3        1        0
  STAGE IV          2        0        0
  STAGE IVA         1        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    17  6    22
  subtype2     1  7    14
  subtype3     3 17    27
D2V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       17        1        3
  T2           6        7       17
  T3+T4       22       14       27
[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"
          vv
clus       N0 N1 N2 N3
  subtype1 19 20  3  3
  subtype2 10  7  2  1
  subtype3 30 14  3  0
D2V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       19       10       30
  N1       20        7       14
  N2        3        2        3
  N3        3        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 30  1   2  9
  subtype2 18  0   0  4
  subtype3 42  0   0  4
D2V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        30       18       42
  M1         1        0        0
  M1A        2        0        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 46
  subtype2  3 21
  subtype3  6 42
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   46
  subtype2    3   21
  subtype3    6   42
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        9        3        6
  MALE         46       21       42
[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     0                         0    51
  subtype2     7                         0    16
  subtype3    29                         2    17
D2V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            0        7       29
  BLACK OR AFRICAN AMERICAN        0        0        2
  WHITE                           51       16       17
[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  7  5
  subtype2 18  4
  subtype3  5  1
  subtype4 14 10
subtype1 subtype2 subtype3 subtype4 
      12       22        6       24 
subtype1 subtype2 subtype3 subtype4 
       5        4        1       10 
$subtype1
TCGA-IG-A3I8 TCGA-IG-A3YA TCGA-IG-A4QT TCGA-IG-A625 TCGA-L5-A43H TCGA-L5-A4OM 
       33.27        20.78         0.99         0.36         0.30         4.08 
TCGA-LN-A49K TCGA-LN-A49L TCGA-LN-A49V TCGA-LN-A49Y TCGA-LN-A4A5 TCGA-LN-A4A8 
        0.07        10.45         0.10         0.07         0.10         0.07 

$subtype2
TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A50L TCGA-IG-A5B8 TCGA-L5-A43J TCGA-LN-A49M 
       20.09         0.85         0.53         0.79         4.31         0.16 
TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49U TCGA-LN-A49W TCGA-LN-A49X 
        0.07         0.33         0.10         0.07         0.07         0.10 
TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A9 TCGA-LN-A4MR 
        0.13         0.07         0.10         0.10         0.07         0.07 
TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW 
        0.20         1.18         5.16        14.01 

$subtype3
TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-LN-A49S TCGA-LN-A4MQ TCGA-Q9-A6FW TCGA-R6-A6L4 
       20.12         0.03         0.13         0.10         3.78        14.70 

$subtype4
TCGA-IG-A4QS TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OF 
        0.26         3.16         3.45         8.94         3.52         3.68 
TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP 
        3.35        19.50         6.41        18.35         3.32         7.17 
TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW 
        1.38         3.16        30.74         4.90        29.00         7.13 
TCGA-L5-A4OX TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-S8-A6BV 
        7.43        17.62         8.02         7.59         5.06         8.78 

subtype1 subtype2 subtype3 subtype4 
    0.07     0.07     0.03     0.26 
subtype1 subtype2 subtype3 subtype4 
   33.27    20.09    20.12    30.74 
subtype1 subtype2 subtype3 subtype4 
   0.330    0.145    1.955    6.770 
[1] "0.1 - 33.3 (0.3)" "0.1 - 20.1 (0.1)" "0.0 - 20.1 (2.0)" "0.3 - 30.7 (6.8)"
D3V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       0        1        0        0         9         0         1
  subtype2       0        0        2        1         9         4         4
  subtype3       0        0        0        0         1         1         1
  subtype4       4        2        0        0         2         5         0
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1          1          1          0        0
  subtype2          2          1          0        0
  subtype3          1          1          0        0
  subtype4          2          2          1        1
D3V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           0        0        0        4
  STAGE IA          1        0        0        2
  STAGE IB          0        2        0        0
  STAGE II          0        1        0        0
  STAGE IIA         9        9        1        2
  STAGE IIB         0        4        1        5
  STAGE III         1        4        1        0
  STAGE IIIA        1        2        1        2
  STAGE IIIB        1        1        1        2
  STAGE IIIC        0        0        0        1
  STAGE IV          0        0        0        1
[1] 11  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     1  3     9
  subtype2     0  8    15
  subtype3     0  1     4
  subtype4     8  4     8
D3V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1        1        0        0        8
  T2           3        8        1        4
  T3+T4        9       15        4        8
[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"
          vv
clus       N0 N1 N2 N3
  subtype1 11  1  1  0
  subtype2 15  7  1  0
  subtype3  1  3  1  0
  subtype4  8  7  4  1
D3V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       11       15        1        8
  N1        1        7        3        7
  N2        1        1        1        4
  N3        0        0        0        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 M1A MX
  subtype1 12   0  0
  subtype2 21   0  2
  subtype3  5   0  0
  subtype4 11   1  5
D3V6, multiclass
     clus
vv    subtype1 subtype2 subtype3 subtype4
  M0        12       21        5       11
  M1A        0        0        0        1
  MX         0        2        0        5
[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"
D3V7, binary
          cls
clus        0  1
  subtype1  2 11
  subtype2  1 22
  subtype3  0  6
  subtype4  7 17
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   11
  subtype2    1   22
  subtype3    0    6
  subtype4    7   17
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        2        1        0        7
  MALE         11       22        6       17
[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"
D3V8, continuous
          vv
clus       ASIAN WHITE
  subtype1     8     5
  subtype2    17     6
  subtype3     2     4
  subtype4     0    21
D3V9, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  ASIAN        8       17        2        0
  WHITE        5        6        4       21
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(4) Variable = MRNASEQ_CHIERARCHICAL
D4V1, survival
          sevent
clus2       0  1
  subtype1  7  4
  subtype2 15  4
  subtype3 16 10
  subtype4  6  2
subtype1 subtype2 subtype3 subtype4 
      11       19       26        8 
subtype1 subtype2 subtype3 subtype4 
       4        4       10        2 
$subtype1
TCGA-IG-A3I8 TCGA-IG-A3YA TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A625 TCGA-L5-A43H 
       33.27        20.78        20.12         0.03         0.36         0.30 
TCGA-L5-A4OM TCGA-LN-A49K TCGA-LN-A49S TCGA-LN-A4A3 TCGA-LN-A4MQ 
        4.08         0.07         0.13         0.07         0.10 

$subtype2
TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A50L TCGA-IG-A5B8 TCGA-L5-A43J TCGA-LN-A49M 
       20.09         0.85         0.53         0.79         4.31         0.16 
TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49U TCGA-LN-A49X TCGA-LN-A4A2 
        0.07         0.33         0.10         0.07         0.10         0.13 
TCGA-LN-A4A4 TCGA-LN-A4A9 TCGA-LN-A4MR TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU 
        0.10         0.07         0.07         0.20         1.18         5.16 
TCGA-S8-A6BW 
       14.01 

$subtype3
TCGA-IG-A4QS TCGA-L5-A43C TCGA-L5-A43E TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OF 
        0.26         3.16         3.45         8.94         3.52         3.68 
TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP 
        3.35        19.50         6.41        18.35         3.32         7.17 
TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW 
        1.38         3.16        30.74         4.90        29.00         7.13 
TCGA-L5-A4OX TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ 
        7.43        17.62         3.78         8.02         7.59         5.06 
TCGA-R6-A6L4 TCGA-S8-A6BV 
       14.70         8.78 

$subtype4
TCGA-IG-A4QT TCGA-LN-A49L TCGA-LN-A49V TCGA-LN-A49W TCGA-LN-A49Y TCGA-LN-A4A5 
        0.99        10.45         0.10         0.07         0.07         0.10 
TCGA-LN-A4A6 TCGA-LN-A4A8 
        0.10         0.07 

subtype1 subtype2 subtype3 subtype4 
    0.03     0.07     0.26     0.07 
subtype1 subtype2 subtype3 subtype4 
   33.27    20.09    30.74    10.45 
subtype1 subtype2 subtype3 subtype4 
    0.30     0.20     6.77     0.10 
[1] "0.0 - 33.3 (0.3)" "0.1 - 20.1 (0.2)" "0.3 - 30.7 (6.8)" "0.1 - 10.4 (0.1)"
D4V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       0        1        0        0         4         1         3
  subtype2       0        0        2        0         9         4         2
  subtype3       4        2        0        0         2         5         0
  subtype4       0        0        0        1         6         0         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV
  subtype1          2          1          0        0
  subtype2          2          1          0        0
  subtype3          2          3          1        1
  subtype4          0          0          0        0
D4V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           0        0        4        0
  STAGE IA          1        0        2        0
  STAGE IB          0        2        0        0
  STAGE II          0        0        0        1
  STAGE IIA         4        9        2        6
  STAGE IIB         1        4        5        0
  STAGE III         3        2        0        1
  STAGE IIIA        2        2        2        0
  STAGE IIIB        1        1        3        0
  STAGE IIIC        0        0        1        0
  STAGE IV          0        0        1        0
[1] 11  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     1  1    10
  subtype2     0  7    13
  subtype3     8  4     9
  subtype4     0  4     4
D4V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1        1        0        8        0
  T2           1        7        4        4
  T3+T4       10       13        9        4
[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"
          vv
clus       N0 N1 N2 N3
  subtype1  6  5  1  0
  subtype2 14  5  1  0
  subtype3  8  7  5  1
  subtype4  7  1  0  0
D4V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0        6       14        8        7
  N1        5        5        7        1
  N2        1        1        5        0
  N3        0        0        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 M1A MX
  subtype1 11   0  0
  subtype2 18   0  2
  subtype3 12   1  5
  subtype4  8   0  0
D4V6, multiclass
     clus
vv    subtype1 subtype2 subtype3 subtype4
  M0        11       18       12        8
  M1A        0        0        1        0
  MX         0        2        5        0
[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"
D4V7, binary
          cls
clus        0  1
  subtype1  2 10
  subtype2  1 19
  subtype3  7 19
  subtype4  0  8
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    2   10
  subtype2    1   19
  subtype3    7   19
  subtype4    0    8
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        2        1        7        0
  MALE         10       19       19        8
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D4V8, continuous
          vv
clus       ASIAN WHITE
  subtype1     6     6
  subtype2    14     6
  subtype3     0    23
  subtype4     7     1
D4V9, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  ASIAN        6       14        0        7
  WHITE        6        6       23        1
[1] 2 4
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"

Clustering(5) Variable = MIRSEQ_CNMF
D5V1, survival
          sevent
clus2       0  1
  subtype1 39 21
  subtype2 34 13
  subtype3  6  3
subtype1 subtype2 subtype3 
      60       47        9 
subtype1 subtype2 subtype3 
      21       13        3 
$subtype1
TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-L5-A43C 
        0.26       122.10        60.39        42.77        25.41         3.16 
TCGA-L5-A43E TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH 
        3.45         8.94         3.52         3.68         3.35        19.50 
TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OO TCGA-L5-A4OP TCGA-L5-A4OQ 
        8.78         6.41        18.35         3.32         7.17         1.38 
TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A4OW TCGA-L5-A4OX 
        3.16        30.74         4.90        29.00         7.13         7.43 
TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A893 TCGA-L5-A8NE TCGA-L5-A8NF 
        2.60         0.36         3.95         3.02        55.50         2.66 
TCGA-L5-A8NG TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM 
       35.97        12.92        13.48        16.47        13.22         7.76 
TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NV TCGA-L5-A8NW 
        5.42         8.71        13.41        27.12        52.57        46.09 
TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-Q9-A6FW TCGA-R6-A6DN TCGA-R6-A6DQ TCGA-R6-A6KZ 
       10.36        17.62         3.78         8.02         7.59         5.06 
TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 TCGA-R6-A6Y2 
       14.70         7.04        29.59         6.35        53.95         9.30 
TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASX TCGA-ZR-A9CJ 
        7.00         8.78         5.29         4.80         4.44        18.12 

$subtype2
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A50L 
       33.27        20.09         0.85        20.12         0.03         0.53 
TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97H 
       17.03         0.79         0.36         0.13         0.46         0.43 
TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-L5-A43J TCGA-L5-A4OM 
       44.75        53.85         3.68        41.52         4.31         4.08 
TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-LN-A49K TCGA-LN-A49L 
       25.12         7.40        13.55        21.37         0.07        10.45 
TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U 
        0.16         0.07         0.33         0.10         0.13         0.07 
TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 
        0.07         0.10         0.07         0.13         0.07         0.10 
TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR 
        0.10         0.10         0.07         0.07         0.10         0.07 
TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-AASV 
        0.20         1.18         5.16        14.01         8.48 

$subtype3
TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4QT TCGA-IG-A7DP TCGA-KH-A6WC TCGA-L5-A43H 
       20.78         2.63         0.99         1.12         6.21         0.30 
TCGA-L5-A88S TCGA-L5-A88T TCGA-L5-A8NU 
        6.94         8.71        83.24 

subtype1 subtype2 subtype3 
    0.26     0.03     0.30 
subtype1 subtype2 subtype3 
  122.10    53.85    83.24 
subtype1 subtype2 subtype3 
    7.89     0.43     6.21 
[1] "0.3 - 122.1 (7.9)" "0.0 - 53.9 (0.4)"  "0.3 - 83.2 (6.2)" 
D5V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        2        0         3        12         7
  subtype2       0        1        2        1        27         9         8
  subtype3       0        1        1        0         3         1         1
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          3          4        2         1
  subtype2          3          3          0        0         0
  subtype3          3          0          0        0         0
D5V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           7        0        0
  STAGE IA          2        1        1
  STAGE IB          2        2        1
  STAGE II          0        1        0
  STAGE IIA         3       27        3
  STAGE IIB        12        9        1
  STAGE III         7        8        1
  STAGE IIIA        2        3        3
  STAGE IIIB        3        3        0
  STAGE IIIC        4        0        0
  STAGE IV          2        0        0
  STAGE IVA         1        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    17  8    24
  subtype2     3 20    31
  subtype3     1  2     7
D5V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       17        3        1
  T2           8       20        2
  T3+T4       24       31        7
[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"
          vv
clus       N0 N1 N2 N3
  subtype1 19 21  5  4
  subtype2 33 17  3  0
  subtype3  6  3  0  0
D5V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       19       33        6
  N1       21       17        3
  N2        5        3        0
  N3        4        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 32  1   2 11
  subtype2 49  0   0  4
  subtype3  8  0   0  2
D5V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        32       49        8
  M1         1        0        0
  M1A        2        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 49
  subtype2  6 48
  subtype3  1  9
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   49
  subtype2    6   48
  subtype3    1    9
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       11        6        1
  MALE         49       48        9
[1] 2 3
[1] TRUE
[1] "dimension of contingency table is larger than 2 by 2 --- so will do fisher test with simulate.p.value=TRUE"
D5V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    55
  subtype2    34                         1    19
  subtype3     1                         0     9
D5V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            0       34        1
  BLACK OR AFRICAN AMERICAN        0        1        0
  WHITE                           55       19        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 27 17
  subtype2 14  6
  subtype3 22  8
  subtype4 16  6
subtype1 subtype2 subtype3 subtype4 
      44       20       30       22 
subtype1 subtype2 subtype3 subtype4 
      17        6        8        6 
$subtype1
TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-L5-A43E TCGA-L5-A4OE 
        0.26       122.10        60.39        42.77         3.45         3.52 
TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON 
        3.68         3.35        19.50         8.78         6.41        18.35 
TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OW TCGA-L5-A4OX 
        7.17         1.38         3.16        30.74         7.13         7.43 
TCGA-L5-A88V TCGA-L5-A88Y TCGA-L5-A891 TCGA-L5-A8NE TCGA-L5-A8NF TCGA-L5-A8NH 
        2.60         0.36         3.95        55.50         2.66        12.92 
TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NM TCGA-L5-A8NN TCGA-L5-A8NR TCGA-L5-A8NW 
       13.48        16.47         7.76         5.42         8.71        46.09 
TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG 
       10.36        17.62         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-AASX TCGA-ZR-A9CJ 
        4.44        18.12 

$subtype2
TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A938 TCGA-L5-A43C TCGA-L5-A43M TCGA-L5-A4OO 
        0.99         1.12        25.41         3.16         8.94         3.32 
TCGA-L5-A4OT TCGA-L5-A4OU TCGA-L5-A88T TCGA-L5-A893 TCGA-L5-A8NG TCGA-L5-A8NL 
        4.90        29.00         8.71         3.02        35.97        13.22 
TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU TCGA-L5-A8NV TCGA-Q9-A6FW TCGA-R6-A6DN 
       13.41        27.12        83.24        52.57         3.78         8.02 
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-A4P3 
       33.27        20.09         0.85        20.78         2.63         0.03 
TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A97H TCGA-JY-A6FE TCGA-KH-A6WC TCGA-L5-A43H 
        0.36         0.13         0.43         3.68         6.21         0.30 
TCGA-L5-A43J TCGA-L5-A88S TCGA-L5-A88Z TCGA-LN-A49K TCGA-LN-A49N TCGA-LN-A49R 
        4.31         6.94         7.40         0.07         0.07         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-AASV 
        0.10         0.07         0.20         5.16        14.01         8.48 

$subtype4
TCGA-IG-A3YC TCGA-IG-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A8O2 TCGA-JY-A6FA 
       20.12         0.53        17.03         0.79         0.46        44.75 
TCGA-JY-A6FD TCGA-JY-A6FG TCGA-L5-A4OM TCGA-L5-A88W TCGA-L5-A8NK TCGA-L5-A8NQ 
       53.85        41.52         4.08        25.12        13.55        21.37 
TCGA-LN-A49L TCGA-LN-A49M TCGA-LN-A49O TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49Y 
       10.45         0.16         0.33         0.13         0.07         0.07 
TCGA-LN-A4A3 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A5U7 
        0.07         0.07         0.07         1.18 

subtype1 subtype2 subtype3 subtype4 
    0.26     0.99     0.03     0.07 
subtype1 subtype2 subtype3 subtype4 
  122.10    83.24    33.27    53.85 
subtype1 subtype2 subtype3 subtype4 
   7.300    8.745    0.330    0.985 
[1] "0.3 - 122.1 (7.3)" "1.0 - 83.2 (8.7)"  "0.0 - 33.3 (0.3)" 
[4] "0.1 - 53.9 (1.0)" 
D6V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       6        2        2        0         1         9         5
  subtype2       1        0        0        0         4         4         2
  subtype3       0        1        2        1        12         7         7
  subtype4       0        1        1        0        16         2         2
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          1          2          3        1         1
  subtype2          2          1          1        1         0
  subtype3          3          2          0        0         0
  subtype4          2          1          0        0         0
D6V3, multiclass
            clus
vv           subtype1 subtype2 subtype3 subtype4
  STAGE I           6        1        0        0
  STAGE IA          2        0        1        1
  STAGE IB          2        0        2        1
  STAGE II          0        0        1        0
  STAGE IIA         1        4       12       16
  STAGE IIB         9        4        7        2
  STAGE III         5        2        7        2
  STAGE IIIA        1        2        3        2
  STAGE IIIB        2        1        2        1
  STAGE IIIC        3        1        0        0
  STAGE IV          1        1        0        0
  STAGE IVA         1        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    16  8    12
  subtype2     1  2    14
  subtype3     2 10    23
  subtype4     2 10    13
D6V4, multiclass
       clus
vv      subtype1 subtype2 subtype3 subtype4
  T0+T1       16        1        2        2
  T2           8        2       10       10
  T3+T4       12       14       23       13
[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"
          vv
clus       N0 N1 N2 N3
  subtype1 13 17  3  3
  subtype2  8  5  2  1
  subtype3 19 13  2  0
  subtype4 18  6  1  0
D6V5, multiclass
    clus
vv   subtype1 subtype2 subtype3 subtype4
  N0       13        8       19       18
  N1       17        5       13        6
  N2        3        2        2        1
  N3        3        1        0        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 22  1   1  9
  subtype2 13  0   1  3
  subtype3 31  0   0  4
  subtype4 23  0   0  1
D6V6, multiclass
     clus
vv    subtype1 subtype2 subtype3 subtype4
  M0        22       13       31       23
  M1         1        0        0        0
  M1A        1        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  8 36
  subtype2  4 16
  subtype3  3 32
  subtype4  3 22
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    8   36
  subtype2    4   16
  subtype3    3   32
  subtype4    3   22
        clus
vv       subtype1 subtype2 subtype3 subtype4
  FEMALE        8        4        3        3
  MALE         36       16       32       22
[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     0                         0    40
  subtype2     0                         0    19
  subtype3    18                         1    16
  subtype4    17                         0     8
D6V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3 subtype4
  ASIAN                            0        0       18       17
  BLACK OR AFRICAN AMERICAN        0        0        1        0
  WHITE                           40       19       16        8
[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 35 21
  subtype2 31 12
  subtype3 13  4
subtype1 subtype2 subtype3 
      56       43       17 
subtype1 subtype2 subtype3 
      21       12        4 
$subtype1
TCGA-IG-A4QS TCGA-JY-A6F8 TCGA-JY-A6FB TCGA-JY-A6FH TCGA-JY-A938 TCGA-L5-A43C 
        0.26       122.10        60.39        42.77        25.41         3.16 
TCGA-L5-A43E TCGA-L5-A43M TCGA-L5-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH 
        3.45         8.94         3.52         3.68         3.35        19.50 
TCGA-L5-A4OI TCGA-L5-A4OJ TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR 
        8.78         6.41        18.35         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-A8NE TCGA-L5-A8NF TCGA-L5-A8NG 
        0.36         3.95         3.02        55.50         2.66        35.97 
TCGA-L5-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NL TCGA-L5-A8NM TCGA-L5-A8NN 
       12.92        13.48        16.47        13.22         7.76         5.42 
TCGA-L5-A8NR TCGA-L5-A8NV TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6DN 
        8.71        52.57        46.09        10.36        17.62         8.02 
TCGA-R6-A6DQ TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG TCGA-R6-A6XQ 
        7.59         5.06        14.70         7.04        29.59         6.35 
TCGA-R6-A6Y0 TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-S8-A6BV TCGA-V5-A7RB TCGA-V5-A7RE 
       53.95         9.30         7.00         8.78         5.29         4.80 
TCGA-V5-AASX TCGA-ZR-A9CJ 
        4.44        18.12 

$subtype2
TCGA-IG-A3I8 TCGA-IG-A3QL TCGA-IG-A3Y9 TCGA-IG-A3YC TCGA-IG-A4P3 TCGA-IG-A50L 
       33.27        20.09         0.85        20.12         0.03         0.53 
TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A625 TCGA-IG-A6QS TCGA-IG-A8O2 TCGA-IG-A97H 
       17.03         0.79         0.36         0.13         0.46         0.43 
TCGA-JY-A6FA TCGA-JY-A6FD TCGA-JY-A6FE TCGA-JY-A6FG TCGA-L5-A43J TCGA-L5-A4OM 
       44.75        53.85         3.68        41.52         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-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U TCGA-LN-A49X TCGA-LN-A49Y 
        0.33         0.10         0.13         0.07         0.10         0.07 
TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 
        0.13         0.07         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-AASV 
        8.48 

$subtype3
TCGA-IG-A3YA TCGA-IG-A3YB TCGA-IG-A4QT TCGA-IG-A7DP TCGA-KH-A6WC TCGA-L5-A43H 
       20.78         2.63         0.99         1.12         6.21         0.30 
TCGA-L5-A4OO TCGA-L5-A88S TCGA-L5-A88T TCGA-L5-A8NQ TCGA-L5-A8NS TCGA-L5-A8NT 
        3.32         6.94         8.71        21.37        13.41        27.12 
TCGA-L5-A8NU TCGA-LN-A49N TCGA-LN-A49W TCGA-LN-A4A5 TCGA-Q9-A6FW 
       83.24         0.07         0.07         0.10         3.78 

subtype1 subtype2 subtype3 
    0.26     0.03     0.07 
subtype1 subtype2 subtype3 
  122.10    53.85    83.24 
subtype1 subtype2 subtype3 
    7.89     0.46     3.78 
[1] "0.3 - 122.1 (7.9)" "0.0 - 53.9 (0.5)"  "0.1 - 83.2 (3.8)" 
D7V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       7        2        2        0         3        10         7
  subtype2       0        1        2        1        25         8         7
  subtype3       0        1        1        0         5         4         2
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          2          2          3        2         1
  subtype2          3          3          0        0         0
  subtype3          3          1          1        0         0
D7V3, multiclass
            clus
vv           subtype1 subtype2 subtype3
  STAGE I           7        0        0
  STAGE IA          2        1        1
  STAGE IB          2        2        1
  STAGE II          0        1        0
  STAGE IIA         3       25        5
  STAGE IIB        10        8        4
  STAGE III         7        7        2
  STAGE IIIA        2        3        3
  STAGE IIIB        2        3        1
  STAGE IIIC        3        0        1
  STAGE IV          2        0        0
  STAGE IVA         1        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    17  8    20
  subtype2     3 17    30
  subtype3     1  5    12
D7V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       17        3        1
  T2           8       17        5
  T3+T4       20       30       12
[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"
          vv
clus       N0 N1 N2 N3
  subtype1 17 21  4  3
  subtype2 31 15  3  0
  subtype3 10  5  1  1
D7V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       17       31       10
  N1       21       15        5
  N2        4        3        1
  N3        3        0        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 28  1   2 11
  subtype2 45  0   0  4
  subtype3 16  0   0  2
D7V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        28       45       16
  M1         1        0        0
  M1A        2        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"
D7V7, binary
          cls
clus        0  1
  subtype1 11 45
  subtype2  6 44
  subtype3  1 17
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1   11   45
  subtype2    6   44
  subtype3    1   17
        clus
vv       subtype1 subtype2 subtype3
  FEMALE       11        6        1
  MALE         45       44       17
[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"
D7V8, continuous
          vv
clus       ASIAN BLACK OR AFRICAN AMERICAN WHITE
  subtype1     0                         0    51
  subtype2    31                         1    18
  subtype3     4                         0    14
D7V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            0       31        4
  BLACK OR AFRICAN AMERICAN        0        1        0
  WHITE                           51       18       14
[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(8) Variable = MIRSEQ_MATURE_CHIERARCHICAL
D8V1, survival
          sevent
clus2       0  1
  subtype1 28 20
  subtype2 12  3
  subtype3 39 14
subtype1 subtype2 subtype3 
      48       15       53 
subtype1 subtype2 subtype3 
      20        3       14 
$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-A4OE TCGA-L5-A4OF TCGA-L5-A4OG TCGA-L5-A4OH TCGA-L5-A4OI TCGA-L5-A4OJ 
        3.52         3.68         3.35        19.50         8.78         6.41 
TCGA-L5-A4ON TCGA-L5-A4OP TCGA-L5-A4OQ TCGA-L5-A4OR TCGA-L5-A4OS TCGA-L5-A4OT 
       18.35         7.17         1.38         3.16        30.74         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-A8NH TCGA-L5-A8NI TCGA-L5-A8NJ TCGA-L5-A8NM TCGA-L5-A8NN 
        2.66        12.92        13.48        16.47         7.76         5.42 
TCGA-L5-A8NR TCGA-L5-A8NW TCGA-L7-A6VZ TCGA-M9-A5M8 TCGA-R6-A6DN TCGA-R6-A6DQ 
        8.71        46.09        10.36        17.62         8.02         7.59 
TCGA-R6-A6KZ TCGA-R6-A6L4 TCGA-R6-A6L6 TCGA-R6-A6XG TCGA-R6-A6XQ TCGA-R6-A6Y0 
        5.06        14.70         7.04        29.59         6.35        53.95 
TCGA-R6-A6Y2 TCGA-RE-A7BO TCGA-V5-A7RB TCGA-V5-A7RE TCGA-V5-AASX TCGA-ZR-A9CJ 
        9.30         7.00         5.29         4.80         4.44        18.12 

$subtype2
TCGA-IG-A4QT TCGA-IG-A7DP TCGA-JY-A938 TCGA-L5-A43M TCGA-L5-A4OO TCGA-L5-A4OU 
        0.99         1.12        25.41         8.94         3.32        29.00 
TCGA-L5-A893 TCGA-L5-A8NG TCGA-L5-A8NL TCGA-L5-A8NS TCGA-L5-A8NT TCGA-L5-A8NU 
        3.02        35.97        13.22        13.41        27.12        83.24 
TCGA-L5-A8NV TCGA-Q9-A6FW TCGA-S8-A6BV 
       52.57         3.78         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-A50L TCGA-IG-A51D TCGA-IG-A5B8 TCGA-IG-A625 TCGA-IG-A6QS 
        0.03         0.53        17.03         0.79         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        53.85         3.68        41.52 
TCGA-KH-A6WC TCGA-L5-A43H TCGA-L5-A43J TCGA-L5-A4OM TCGA-L5-A88S TCGA-L5-A88T 
        6.21         0.30         4.31         4.08         6.94         8.71 
TCGA-L5-A88W TCGA-L5-A88Z TCGA-L5-A8NK TCGA-L5-A8NQ TCGA-LN-A49K TCGA-LN-A49L 
       25.12         7.40        13.55        21.37         0.07        10.45 
TCGA-LN-A49M TCGA-LN-A49N TCGA-LN-A49O TCGA-LN-A49R TCGA-LN-A49S TCGA-LN-A49U 
        0.16         0.07         0.33         0.10         0.13         0.07 
TCGA-LN-A49W TCGA-LN-A49X TCGA-LN-A49Y TCGA-LN-A4A2 TCGA-LN-A4A3 TCGA-LN-A4A4 
        0.07         0.10         0.07         0.13         0.07         0.10 
TCGA-LN-A4A5 TCGA-LN-A4A6 TCGA-LN-A4A8 TCGA-LN-A4A9 TCGA-LN-A4MQ TCGA-LN-A4MR 
        0.10         0.10         0.07         0.07         0.10         0.07 
TCGA-LN-A5U6 TCGA-LN-A5U7 TCGA-Q9-A6FU TCGA-S8-A6BW TCGA-V5-AASV 
        0.20         1.18         5.16        14.01         8.48 

subtype1 subtype2 subtype3 
    0.26     0.99     0.03 
subtype1 subtype2 subtype3 
  122.10    83.24    53.85 
subtype1 subtype2 subtype3 
    7.30    13.22     0.53 
[1] "0.3 - 122.1 (7.3)" "1.0 - 83.2 (13.2)" "0.0 - 53.9 (0.5)" 
D8V2, continuous
          vv
clus       STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III
  subtype1       6        2        2        0         1         9         5
  subtype2       1        0        0        0         4         3         2
  subtype3       0        2        3        1        28        10         9
          vv
clus       STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA
  subtype1          1          2          3        2         1
  subtype2          2          1          1        0         0
  subtype3          5          3          0        0         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       28
  STAGE IIB         9        3       10
  STAGE III         5        2        9
  STAGE IIIA        1        2        5
  STAGE IIIB        2        1        3
  STAGE IIIC        3        1        0
  STAGE IV          2        0        0
  STAGE IVA         1        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    16  8    13
  subtype2     1  1    13
  subtype3     4 21    36
D8V4, multiclass
       clus
vv      subtype1 subtype2 subtype3
  T0+T1       16        1        4
  T2           8        1       21
  T3+T4       13       13       36
[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"
          vv
clus       N0 N1 N2 N3
  subtype1 13 18  3  3
  subtype2  8  3  2  1
  subtype3 37 20  3  0
D8V5, multiclass
    clus
vv   subtype1 subtype2 subtype3
  N0       13        8       37
  N1       18        3       20
  N2        3        2        3
  N3        3        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 22  1   2  9
  subtype2 12  0   0  3
  subtype3 55  0   0  5
D8V6, multiclass
     clus
vv    subtype1 subtype2 subtype3
  M0        22       12       55
  M1         1        0        0
  M1A        2        0        0
  MX         9        3        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  9 39
  subtype2  3 12
  subtype3  6 55
[1] "tbl2"
          cls
clus       [,1] [,2]
  subtype1    9   39
  subtype2    3   12
  subtype3    6   55
        clus
vv       subtype1 subtype2 subtype3
  FEMALE        9        3        6
  MALE         39       12       55
[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     0                         0    44
  subtype2     0                         0    14
  subtype3    35                         1    25
D8V9, multiclass
                           clus
vv                          subtype1 subtype2 subtype3
  ASIAN                            0        0       35
  BLACK OR AFRICAN AMERICAN        0        0        1
  WHITE                           44       14       25
[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"
