Correlation between miRseq expression and clinical features
Lung Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C14T6HM4
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C14T6HM4
Overview
Introduction

This pipeline uses various statistical tests to identify miRs whose log2 expression levels correlated to selected clinical features.

Summary

Testing the association between 531 miRs and 15 clinical features across 512 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 12 clinical features related to at least one miRs.

  • 30 miRs correlated to 'DAYS_TO_DEATH_OR_LAST_FUP'.

    • HSA-MIR-101-1 ,  HSA-MIR-31 ,  HSA-MIR-548B ,  HSA-MIR-582 ,  HSA-MIR-29C ,  ...

  • 30 miRs correlated to 'YEARS_TO_BIRTH'.

    • HSA-MIR-9-2 ,  HSA-MIR-9-1 ,  HSA-MIR-130B ,  HSA-MIR-590 ,  HSA-MIR-629 ,  ...

  • 30 miRs correlated to 'PATHOLOGIC_STAGE'.

    • HSA-MIR-101-2 ,  HSA-MIR-150 ,  HSA-MIR-30C-2 ,  HSA-MIR-146A ,  HSA-MIR-664 ,  ...

  • 30 miRs correlated to 'PATHOLOGY_T_STAGE'.

    • HSA-MIR-30C-2 ,  HSA-MIR-101-2 ,  HSA-MIR-451 ,  HSA-MIR-150 ,  HSA-MIR-146A ,  ...

  • 30 miRs correlated to 'PATHOLOGY_N_STAGE'.

    • HSA-MIR-200B ,  HSA-MIR-200A ,  HSA-MIR-660 ,  HSA-MIR-548B ,  HSA-MIR-181C ,  ...

  • 30 miRs correlated to 'GENDER'.

    • HSA-MIR-105-2 ,  HSA-MIR-99A ,  HSA-MIR-361 ,  HSA-MIR-30E ,  HSA-MIR-105-1 ,  ...

  • 9 miRs correlated to 'KARNOFSKY_PERFORMANCE_SCORE'.

    • HSA-MIR-660 ,  HSA-MIR-874 ,  HSA-MIR-616 ,  HSA-MIR-532 ,  HSA-MIR-489 ,  ...

  • 30 miRs correlated to 'HISTOLOGICAL_TYPE'.

    • HSA-MIR-130B ,  HSA-MIR-656 ,  HSA-MIR-18A ,  HSA-MIR-338 ,  HSA-MIR-200A ,  ...

  • 30 miRs correlated to 'NUMBER_PACK_YEARS_SMOKED'.

    • HSA-MIR-210 ,  HSA-MIR-339 ,  HSA-MIR-345 ,  HSA-MIR-296 ,  HSA-MIR-590 ,  ...

  • 25 miRs correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

    • HSA-MIR-629 ,  HSA-MIR-508 ,  HSA-MIR-550A-1 ,  HSA-MIR-514-1 ,  HSA-MIR-514-3 ,  ...

  • 9 miRs correlated to 'RESIDUAL_TUMOR'.

    • HSA-MIR-34B ,  HSA-MIR-34A ,  HSA-MIR-34C ,  HSA-MIR-664 ,  HSA-MIR-151 ,  ...

  • 18 miRs correlated to 'RACE'.

    • HSA-MIR-1304 ,  HSA-MIR-3680 ,  HSA-MIR-548J ,  HSA-MIR-3667 ,  HSA-MIR-186 ,  ...

  • No miRs correlated to 'PATHOLOGY_M_STAGE', 'RADIATION_THERAPY', and 'ETHNICITY'.

Results
Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1.  Get Full Table This table shows the clinical features, statistical methods used, and the number of miRs that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.

Clinical feature Statistical test Significant miRs Associated with                 Associated with
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test N=30 shorter survival N=11 longer survival N=19
YEARS_TO_BIRTH Spearman correlation test N=30 older N=7 younger N=23
PATHOLOGIC_STAGE Kruskal-Wallis test N=30        
PATHOLOGY_T_STAGE Spearman correlation test N=30 higher stage N=5 lower stage N=25
PATHOLOGY_N_STAGE Spearman correlation test N=30 higher stage N=13 lower stage N=17
PATHOLOGY_M_STAGE Wilcoxon test   N=0        
GENDER Wilcoxon test N=30 male N=30 female N=0
RADIATION_THERAPY Wilcoxon test   N=0        
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test N=9 higher score N=6 lower score N=3
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
NUMBER_PACK_YEARS_SMOKED Spearman correlation test N=30 higher number_pack_years_smoked N=30 lower number_pack_years_smoked N=0
YEAR_OF_TOBACCO_SMOKING_ONSET Spearman correlation test N=25 higher year_of_tobacco_smoking_onset N=12 lower year_of_tobacco_smoking_onset N=13
RESIDUAL_TUMOR Kruskal-Wallis test N=9        
RACE Kruskal-Wallis test N=18        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

30 miRs related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0-238.3 (median=20)
  censored N = 341
  death N = 170
     
  Significant markers N = 30
  associated with shorter survival 11
  associated with longer survival 19
List of top 10 miRs differentially expressed by 'DAYS_TO_DEATH_OR_LAST_FUP'

Table S2.  Get Full Table List of top 10 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-101-1 0.67 0.0001476 0.041 0.398
HSA-MIR-31 1.12 0.0001557 0.041 0.632
HSA-MIR-548B 0.81 0.0002874 0.051 0.384
HSA-MIR-582 1.18 0.000758 0.086 0.606
HSA-MIR-29C 0.77 0.0009056 0.086 0.411
HSA-MIR-1468 0.82 0.001141 0.086 0.441
HSA-MIR-1293 1.16 0.00123 0.086 0.589
HSA-MIR-1910 1.29 0.001298 0.086 0.614
HSA-MIR-212 1.28 0.001949 0.11 0.572
HSA-MIR-148A 0.79 0.002188 0.12 0.444
Clinical variable #2: 'YEARS_TO_BIRTH'

30 miRs related to 'YEARS_TO_BIRTH'.

Table S3.  Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'

YEARS_TO_BIRTH Mean (SD) 65.29 (10)
  Significant markers N = 30
  pos. correlated 7
  neg. correlated 23
List of top 10 miRs differentially expressed by 'YEARS_TO_BIRTH'

Table S4.  Get Full Table List of top 10 miRs significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-9-2 -0.1807 6.6e-05 0.0172
HSA-MIR-9-1 -0.1781 8.424e-05 0.0172
HSA-MIR-130B -0.1766 9.722e-05 0.0172
HSA-MIR-590 -0.1696 0.0001827 0.0207
HSA-MIR-629 -0.1689 0.000195 0.0207
HSA-MIR-424 -0.1618 0.0003621 0.032
HSA-MIR-18A -0.1572 0.0005341 0.0405
HSA-MIR-96 -0.1551 0.0006327 0.0416
HSA-MIR-30A 0.1538 0.0007048 0.0416
HSA-MIR-345 -0.1516 0.0008429 0.0429
Clinical variable #3: 'PATHOLOGIC_STAGE'

30 miRs related to 'PATHOLOGIC_STAGE'.

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGIC_STAGE'

PATHOLOGIC_STAGE Labels N
  STAGE I 5
  STAGE IA 134
  STAGE IB 139
  STAGE II 1
  STAGE IIA 52
  STAGE IIB 70
  STAGE IIIA 73
  STAGE IIIB 11
  STAGE IV 25
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'PATHOLOGIC_STAGE'

Table S6.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGIC_STAGE'

kruskal_wallis_P Q
HSA-MIR-101-2 5.782e-06 0.00307
HSA-MIR-150 3.517e-05 0.0071
HSA-MIR-30C-2 4.012e-05 0.0071
HSA-MIR-146A 0.0001768 0.0213
HSA-MIR-664 0.0002006 0.0213
HSA-MIR-451 0.0003137 0.0278
HSA-MIR-548B 0.000447 0.0329
HSA-MIR-660 0.0004954 0.0329
HSA-MIR-200A 0.0008789 0.05
HSA-MIR-342 0.0009926 0.05
Clinical variable #4: 'PATHOLOGY_T_STAGE'

30 miRs related to 'PATHOLOGY_T_STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY_T_STAGE'

PATHOLOGY_T_STAGE Mean (SD) 1.83 (0.74)
  N
  T1 169
  T2 274
  T3 47
  T4 19
     
  Significant markers N = 30
  pos. correlated 5
  neg. correlated 25
List of top 10 miRs differentially expressed by 'PATHOLOGY_T_STAGE'

Table S8.  Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY_T_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-30C-2 -0.2351 8.052e-08 3.03e-05
HSA-MIR-101-2 -0.2324 1.141e-07 3.03e-05
HSA-MIR-451 -0.2268 2.308e-07 4.08e-05
HSA-MIR-150 -0.2164 8.294e-07 0.00011
HSA-MIR-146A -0.21 1.767e-06 0.000188
HSA-MIR-342 -0.2028 3.976e-06 3e-04
HSA-MIR-374B -0.2019 4.401e-06 3e-04
HSA-MIR-218-2 -0.2017 4.515e-06 3e-04
HSA-MIR-497 -0.199 6.051e-06 0.000357
HSA-MIR-30B -0.1964 8.043e-06 0.000427
Clinical variable #5: 'PATHOLOGY_N_STAGE'

30 miRs related to 'PATHOLOGY_N_STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY_N_STAGE'

PATHOLOGY_N_STAGE Mean (SD) 0.5 (0.76)
  N
  N0 329
  N1 95
  N2 74
  N3 2
     
  Significant markers N = 30
  pos. correlated 13
  neg. correlated 17
List of top 10 miRs differentially expressed by 'PATHOLOGY_N_STAGE'

Table S10.  Get Full Table List of top 10 miRs significantly correlated to 'PATHOLOGY_N_STAGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-200B -0.1784 6.02e-05 0.0143
HSA-MIR-200A -0.1783 6.07e-05 0.0143
HSA-MIR-660 -0.1735 9.672e-05 0.0143
HSA-MIR-548B -0.178 0.000108 0.0143
HSA-MIR-181C -0.1602 0.0003229 0.0326
HSA-MIR-29C -0.1587 0.0003683 0.0326
HSA-MIR-429 -0.155 0.0005063 0.0384
HSA-MIR-944 0.1548 0.000812 0.0473
HSA-MIR-497 -0.1484 0.0008707 0.0473
HSA-MIR-30B -0.148 0.0009055 0.0473
Clinical variable #6: 'PATHOLOGY_M_STAGE'

No miR related to 'PATHOLOGY_M_STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY_M_STAGE'

PATHOLOGY_M_STAGE Labels N
  class0 346
  class1 23
     
  Significant markers N = 0
Clinical variable #7: 'GENDER'

30 miRs related to 'GENDER'.

Table S12.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 273
  MALE 239
     
  Significant markers N = 30
  Higher in MALE 30
  Higher in FEMALE 0
List of top 10 miRs differentially expressed by 'GENDER'

Table S13.  Get Full Table List of top 10 miRs differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
HSA-MIR-105-2 16195 2.467e-06 0.00131 0.6539
HSA-MIR-99A 25876 5.349e-05 0.00667 0.6034
HSA-MIR-361 25881 5.418e-05 0.00667 0.6033
HSA-MIR-30E 25888 5.515e-05 0.00667 0.6032
HSA-MIR-105-1 16883 6.276e-05 0.00667 0.6278
HSA-MIR-651 25391 0.000177 0.0157 0.5968
HSA-MIR-1298 4610 0.0003813 0.0289 0.6601
HSA-MIR-1911 11229 0.0004736 0.0313 0.6238
HSA-MIR-542 26869 0.0005705 0.0313 0.5882
HSA-MIR-101-1 26942 0.0006701 0.0313 0.5871
Clinical variable #8: 'RADIATION_THERAPY'

No miR related to 'RADIATION_THERAPY'.

Table S14.  Basic characteristics of clinical feature: 'RADIATION_THERAPY'

RADIATION_THERAPY Labels N
  NO 355
  YES 54
     
  Significant markers N = 0
Clinical variable #9: 'KARNOFSKY_PERFORMANCE_SCORE'

9 miRs related to 'KARNOFSKY_PERFORMANCE_SCORE'.

Table S15.  Basic characteristics of clinical feature: 'KARNOFSKY_PERFORMANCE_SCORE'

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 78.52 (29)
  Significant markers N = 9
  pos. correlated 6
  neg. correlated 3
List of 9 miRs differentially expressed by 'KARNOFSKY_PERFORMANCE_SCORE'

Table S16.  Get Full Table List of 9 miRs significantly correlated to 'KARNOFSKY_PERFORMANCE_SCORE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-660 0.3429 7.411e-05 0.0394
HSA-MIR-874 0.2822 0.001247 0.215
HSA-MIR-616 0.2786 0.001452 0.215
HSA-MIR-532 0.2727 0.001844 0.215
HSA-MIR-489 -0.3212 0.002025 0.215
HSA-MIR-183 -0.2587 0.003192 0.259
HSA-MIR-98 -0.2569 0.003415 0.259
HSA-MIR-185 0.2482 0.004733 0.288
HSA-MIR-502 0.2473 0.004884 0.288
Clinical variable #10: 'HISTOLOGICAL_TYPE'

30 miRs related to 'HISTOLOGICAL_TYPE'.

Table S17.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 19
  LUNG ADENOCARCINOMA MIXED SUBTYPE 105
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 319
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 5
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 19
  LUNG CLEAR CELL ADENOCARCINOMA 2
  LUNG MICROPAPILLARY ADENOCARCINOMA 2
  LUNG MUCINOUS ADENOCARCINOMA 2
  LUNG PAPILLARY ADENOCARCINOMA 23
  LUNG SIGNET RING ADENOCARCINOMA 1
  LUNG SOLID PATTERN PREDOMINANT ADENOCARCINOMA 5
  MUCINOUS (COLLOID) CARCINOMA 10
     
  Significant markers N = 30
List of top 10 miRs differentially expressed by 'HISTOLOGICAL_TYPE'

Table S18.  Get Full Table List of top 10 miRs differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
HSA-MIR-130B 1.411e-05 0.00302
HSA-MIR-656 1.51e-05 0.00302
HSA-MIR-18A 1.709e-05 0.00302
HSA-MIR-338 5.131e-05 0.00466
HSA-MIR-200A 5.23e-05 0.00466
HSA-MIR-200B 5.27e-05 0.00466
HSA-LET-7B 8.877e-05 0.00673
HSA-MIR-369 0.0001528 0.0101
HSA-LET-7A-2 0.0002164 0.0113
HSA-MIR-92A-1 0.0002317 0.0113
Clinical variable #11: 'NUMBER_PACK_YEARS_SMOKED'

30 miRs related to 'NUMBER_PACK_YEARS_SMOKED'.

Table S19.  Basic characteristics of clinical feature: 'NUMBER_PACK_YEARS_SMOKED'

NUMBER_PACK_YEARS_SMOKED Mean (SD) 41.77 (27)
  Significant markers N = 30
  pos. correlated 30
  neg. correlated 0
List of top 10 miRs differentially expressed by 'NUMBER_PACK_YEARS_SMOKED'

Table S20.  Get Full Table List of top 10 miRs significantly correlated to 'NUMBER_PACK_YEARS_SMOKED' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-210 0.2386 6.201e-06 0.00261
HSA-MIR-339 0.2321 1.117e-05 0.00261
HSA-MIR-345 0.229 1.473e-05 0.00261
HSA-MIR-296 0.212 6.401e-05 0.00755
HSA-MIR-590 0.2104 7.106e-05 0.00755
HSA-MIR-301A 0.2006 0.0001543 0.0137
HSA-MIR-31 0.2024 0.0001877 0.0142
HSA-MIR-106A 0.1937 0.0002614 0.0173
HSA-MIR-16-2 0.1851 0.0004918 0.0267
HSA-MIR-627 0.1872 0.0005028 0.0267
Clinical variable #12: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

25 miRs related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.

Table S21.  Basic characteristics of clinical feature: 'YEAR_OF_TOBACCO_SMOKING_ONSET'

YEAR_OF_TOBACCO_SMOKING_ONSET Mean (SD) 1964.75 (12)
  Significant markers N = 25
  pos. correlated 12
  neg. correlated 13
List of top 10 miRs differentially expressed by 'YEAR_OF_TOBACCO_SMOKING_ONSET'

Table S22.  Get Full Table List of top 10 miRs significantly correlated to 'YEAR_OF_TOBACCO_SMOKING_ONSET' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-629 0.2101 0.0004752 0.153
HSA-MIR-508 -0.205 0.0006845 0.153
HSA-MIR-550A-1 0.2005 0.0008636 0.153
HSA-MIR-514-1 -0.2 0.001694 0.207
HSA-MIR-514-3 -0.1867 0.004083 0.207
HSA-MIR-128-1 0.1707 0.00468 0.207
HSA-MIR-3676 0.1679 0.005776 0.207
HSA-MIR-509-1 -0.1811 0.005879 0.207
HSA-MIR-509-3 -0.1797 0.005954 0.207
HSA-MIR-7-3 0.1898 0.006173 0.207
Clinical variable #13: 'RESIDUAL_TUMOR'

9 miRs related to 'RESIDUAL_TUMOR'.

Table S23.  Basic characteristics of clinical feature: 'RESIDUAL_TUMOR'

RESIDUAL_TUMOR Labels N
  R0 339
  R1 12
  R2 4
  RX 26
     
  Significant markers N = 9
List of 9 miRs differentially expressed by 'RESIDUAL_TUMOR'

Table S24.  Get Full Table List of 9 miRs differentially expressed by 'RESIDUAL_TUMOR'

kruskal_wallis_P Q
HSA-MIR-34B 0.0001511 0.0629
HSA-MIR-34A 0.0002369 0.0629
HSA-MIR-34C 0.001161 0.172
HSA-MIR-664 0.001297 0.172
HSA-MIR-151 0.002017 0.187
HSA-MIR-181B-2 0.002117 0.187
HSA-MIR-107 0.002868 0.218
HSA-MIR-642A 0.00389 0.258
HSA-MIR-30C-2 0.004962 0.293
Clinical variable #14: 'RACE'

18 miRs related to 'RACE'.

Table S25.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 8
  BLACK OR AFRICAN AMERICAN 51
  WHITE 386
     
  Significant markers N = 18
List of top 10 miRs differentially expressed by 'RACE'

Table S26.  Get Full Table List of top 10 miRs differentially expressed by 'RACE'

kruskal_wallis_P Q
HSA-MIR-1304 2.017e-06 0.00107
HSA-MIR-3680 0.0007666 0.123
HSA-MIR-548J 0.0009043 0.123
HSA-MIR-3667 0.0009288 0.123
HSA-MIR-186 0.001833 0.162
HSA-MIR-3614 0.002331 0.162
HSA-MIR-339 0.002384 0.162
HSA-MIR-589 0.002437 0.162
HSA-MIR-34A 0.00312 0.18
HSA-MIR-552 0.003646 0.18
Clinical variable #15: 'ETHNICITY'

No miR related to 'ETHNICITY'.

Table S27.  Basic characteristics of clinical feature: 'ETHNICITY'

ETHNICITY Labels N
  HISPANIC OR LATINO 7
  NOT HISPANIC OR LATINO 379
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = LUAD-TP.miRseq_RPKM_log2.txt

  • Clinical data file = LUAD-TP.merged_data.txt

  • Number of patients = 512

  • Number of miRs = 531

  • Number of clinical features = 15

Selected clinical features

  • Further details on clinical features selected for this analysis, please find a documentation on selected CDEs (Clinical Data Elements). The first column of the file is a formula to convert values and the second column is a clinical parameter name.

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

Survival analysis

For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels

Correlation analysis

For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)
[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[3] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle