Correlation between miRseq expression and clinical features
Thyroid Adenocarcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1K64GRK
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1K64GRK
Overview
Introduction

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

Summary

Testing the association between 514 miRs and 15 clinical features across 485 samples, statistically thresholded by Q value < 0.05, 14 clinical features related to at least one miRs.

  • 5 miRs correlated to 'Time to Death'.

    • HSA-MIR-376A-1 ,  HSA-MIR-181A-2 ,  HSA-MIR-487A ,  HSA-MIR-425 ,  HSA-MIR-30D

  • 5 miRs correlated to 'AGE'.

    • HSA-MIR-376A-1 ,  HSA-MIR-625 ,  HSA-MIR-181A-2 ,  HSA-MIR-1229 ,  HSA-MIR-539

  • 46 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-139 ,  HSA-MIR-210 ,  HSA-MIR-146B ,  HSA-MIR-126 ,  HSA-MIR-425 ,  ...

  • 16 miRs correlated to 'PATHOLOGY.T.STAGE'.

    • HSA-MIR-139 ,  HSA-MIR-126 ,  HSA-MIR-363 ,  HSA-MIR-3074 ,  HSA-MIR-30C-2 ,  ...

  • 75 miRs correlated to 'PATHOLOGY.N.STAGE'.

    • HSA-MIR-146B ,  HSA-MIR-21 ,  HSA-MIR-204 ,  HSA-MIR-7-2 ,  HSA-MIR-1179 ,  ...

  • 3 miRs correlated to 'PATHOLOGY.M.STAGE'.

    • HSA-MIR-3677 ,  HSA-MIR-589 ,  HSA-MIR-151

  • 2 miRs correlated to 'GENDER'.

    • HSA-MIR-651 ,  HSA-MIR-361

  • 170 miRs correlated to 'HISTOLOGICAL.TYPE'.

    • HSA-MIR-21 ,  HSA-MIR-146B ,  HSA-MIR-7-2 ,  HSA-MIR-204 ,  HSA-MIR-375 ,  ...

  • 10 miRs correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • HSA-MIR-888 ,  HSA-MIR-374A ,  HSA-MIR-660 ,  HSA-MIR-324 ,  HSA-MIR-20B ,  ...

  • 76 miRs correlated to 'EXTRATHYROIDAL.EXTENSION'.

    • HSA-MIR-363 ,  HSA-MIR-30A ,  HSA-MIR-148B ,  HSA-MIR-126 ,  HSA-MIR-758 ,  ...

  • 1 miR correlated to 'COMPLETENESS.OF.RESECTION'.

    • HSA-MIR-139

  • 60 miRs correlated to 'NUMBER.OF.LYMPH.NODES'.

    • HSA-MIR-7-2 ,  HSA-MIR-1179 ,  HSA-MIR-21 ,  HSA-MIR-511-2 ,  HSA-MIR-382 ,  ...

  • 1 miR correlated to 'MULTIFOCALITY'.

    • HSA-MIR-132

  • 2 miRs correlated to 'TUMOR.SIZE'.

    • HSA-MIR-9-2 ,  HSA-MIR-9-1

  • No miRs correlated to 'RADIATIONEXPOSURE'

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 Q value < 0.05.

Clinical feature Statistical test Significant miRs Associated with                 Associated with
Time to Death Cox regression test N=5 shorter survival N=3 longer survival N=2
AGE Spearman correlation test N=5 older N=3 younger N=2
NEOPLASM DISEASESTAGE ANOVA test N=46        
PATHOLOGY T STAGE Spearman correlation test N=16 higher stage N=4 lower stage N=12
PATHOLOGY N STAGE t test N=75 class1 N=41 class0 N=34
PATHOLOGY M STAGE ANOVA test N=3        
GENDER t test N=2 male N=0 female N=2
HISTOLOGICAL TYPE ANOVA test N=170        
RADIATIONS RADIATION REGIMENINDICATION t test N=10 yes N=7 no N=3
RADIATIONEXPOSURE t test   N=0        
EXTRATHYROIDAL EXTENSION ANOVA test N=76        
COMPLETENESS OF RESECTION ANOVA test N=1        
NUMBER OF LYMPH NODES Spearman correlation test N=60 higher number.of.lymph.nodes N=36 lower number.of.lymph.nodes N=24
MULTIFOCALITY t test N=1 unifocal N=0 multifocal N=1
TUMOR SIZE Spearman correlation test N=2 higher tumor.size N=0 lower tumor.size N=2
Clinical variable #1: 'Time to Death'

5 miRs related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0-158.8 (median=15.5)
  censored N = 467
  death N = 14
     
  Significant markers N = 5
  associated with shorter survival 3
  associated with longer survival 2
List of 5 miRs significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 5 miRs significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
HSA-MIR-376A-1 4.2 2.429e-05 0.012 0.885
HSA-MIR-181A-2 0.33 3.736e-05 0.019 0.175
HSA-MIR-487A 2.6 4.87e-05 0.025 0.843
HSA-MIR-425 5.6 7.319e-05 0.037 0.792
HSA-MIR-30D 0.14 7.973e-05 0.041 0.159

Figure S1.  Get High-res Image As an example, this figure shows the association of HSA-MIR-376A-1 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 2.43e-05 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

5 miRs related to 'AGE'.

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

AGE Mean (SD) 47.23 (16)
  Significant markers N = 5
  pos. correlated 3
  neg. correlated 2
List of 5 miRs significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 5 miRs significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-376A-1 0.2611 1.068e-05 0.00549
HSA-MIR-625 -0.1967 1.275e-05 0.00654
HSA-MIR-181A-2 -0.1925 1.96e-05 0.01
HSA-MIR-1229 0.2012 5.274e-05 0.027
HSA-MIR-539 0.1888 8.308e-05 0.0424

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-376A-1 to 'AGE'. P value = 1.07e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

46 miRs related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 274
  STAGE II 51
  STAGE III 106
  STAGE IV 2
  STAGE IVA 44
  STAGE IVC 6
     
  Significant markers N = 46
List of top 10 miRs differentially expressed by 'NEOPLASM.DISEASESTAGE'

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

ANOVA_P Q
HSA-MIR-139 5.764e-13 2.96e-10
HSA-MIR-210 1.265e-10 6.49e-08
HSA-MIR-146B 1.586e-07 8.12e-05
HSA-MIR-126 3.466e-07 0.000177
HSA-MIR-425 3.732e-07 0.00019
HSA-MIR-376C 3.914e-07 0.000199
HSA-MIR-31 4.033e-07 0.000205
HSA-MIR-154 4.403e-07 0.000223
HSA-MIR-369 8.704e-07 0.00044
HSA-MIR-655 9.37e-07 0.000473

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'NEOPLASM.DISEASESTAGE'. P value = 5.76e-13 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

16 miRs related to 'PATHOLOGY.T.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.13 (0.88)
  N
  1 140
  2 162
  3 160
  4 21
     
  Significant markers N = 16
  pos. correlated 4
  neg. correlated 12
List of top 10 miRs significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

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-139 -0.2845 1.904e-10 9.79e-08
HSA-MIR-126 -0.2717 1.279e-09 6.56e-07
HSA-MIR-363 -0.2442 5.649e-08 2.89e-05
HSA-MIR-3074 -0.2062 4.92e-06 0.00251
HSA-MIR-30C-2 -0.2061 4.927e-06 0.00251
HSA-MIR-145 -0.2004 9.041e-06 0.0046
HSA-MIR-7-2 -0.2028 9.161e-06 0.00465
HSA-MIR-20B -0.2002 9.458e-06 0.00479
HSA-MIR-92B 0.1985 1.109e-05 0.00561
HSA-MIR-338 -0.1941 1.747e-05 0.00882

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'PATHOLOGY.T.STAGE'. P value = 1.9e-10 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

75 miRs related to 'PATHOLOGY.N.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 221
  class1 217
     
  Significant markers N = 75
  Higher in class1 41
  Higher in class0 34
List of top 10 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

Table S10.  Get Full Table List of top 10 miRs differentially expressed by 'PATHOLOGY.N.STAGE'

T(pos if higher in 'class1') ttestP Q AUC
HSA-MIR-146B 7.81 6.967e-14 3.58e-11 0.675
HSA-MIR-21 7.61 1.977e-13 1.01e-10 0.6832
HSA-MIR-204 -7.12 4.92e-12 2.52e-09 0.677
HSA-MIR-7-2 -7.1 5.356e-12 2.74e-09 0.6857
HSA-MIR-1179 -6.98 1.205e-11 6.14e-09 0.6852
HSA-MIR-222 6.82 4.217e-11 2.15e-08 0.6569
HSA-MIR-511-2 6.45 3.08e-10 1.56e-07 0.6703
HSA-MIR-221 6.34 7.455e-10 3.78e-07 0.6363
HSA-MIR-3074 -6.15 1.821e-09 9.21e-07 0.6638
HSA-MIR-375 6.13 2.215e-09 1.12e-06 0.6382

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-MIR-146B to 'PATHOLOGY.N.STAGE'. P value = 6.97e-14 with T-test analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

3 miRs related to 'PATHOLOGY.M.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 265
  M1 9
  MX 210
     
  Significant markers N = 3
List of 3 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of 3 miRs differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
HSA-MIR-3677 7.207e-06 0.0037
HSA-MIR-589 6.01e-05 0.0308
HSA-MIR-151 7.825e-05 0.0401

Figure S6.  Get High-res Image As an example, this figure shows the association of HSA-MIR-3677 to 'PATHOLOGY.M.STAGE'. P value = 7.21e-06 with ANOVA analysis.

Clinical variable #7: 'GENDER'

2 miRs related to 'GENDER'.

Table S13.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 355
  MALE 130
     
  Significant markers N = 2
  Higher in MALE 0
  Higher in FEMALE 2
List of 2 miRs differentially expressed by 'GENDER'

Table S14.  Get Full Table List of 2 miRs differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
HSA-MIR-651 -5.26 3.578e-07 0.000184 0.6564
HSA-MIR-361 -4.49 1.072e-05 0.0055 0.6188

Figure S7.  Get High-res Image As an example, this figure shows the association of HSA-MIR-651 to 'GENDER'. P value = 3.58e-07 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

170 miRs related to 'HISTOLOGICAL.TYPE'.

Table S15.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  OTHER SPECIFY 9
  THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL 342
  THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) 99
  THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) 35
     
  Significant markers N = 170
List of top 10 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

Table S16.  Get Full Table List of top 10 miRs differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
HSA-MIR-21 9.665e-41 4.97e-38
HSA-MIR-146B 1.077e-32 5.53e-30
HSA-MIR-7-2 2.784e-24 1.43e-21
HSA-MIR-204 1.99e-21 1.02e-18
HSA-MIR-375 3.526e-21 1.8e-18
HSA-MIR-1179 9.677e-21 4.93e-18
HSA-MIR-511-2 1.492e-20 7.58e-18
HSA-MIR-345 1.547e-20 7.84e-18
HSA-MIR-31 2.22e-20 1.12e-17
HSA-MIR-511-1 7.884e-20 3.98e-17

Figure S8.  Get High-res Image As an example, this figure shows the association of HSA-MIR-21 to 'HISTOLOGICAL.TYPE'. P value = 9.66e-41 with ANOVA analysis.

Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

10 miRs related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S17.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 14
  YES 471
     
  Significant markers N = 10
  Higher in YES 7
  Higher in NO 3
List of 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S18.  Get Full Table List of 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-888 9.81 1.002e-10 5.01e-08 0.8819
HSA-MIR-374A -8.74 2.741e-07 0.000137 0.917
HSA-MIR-660 7.95 9.306e-07 0.000463 0.8857
HSA-MIR-324 6.54 9.051e-06 0.0045 0.8444
HSA-MIR-20B 6.33 1.422e-05 0.00705 0.8378
HSA-MIR-3130-1 -5.5 3.8e-05 0.0188 0.7427
HSA-MIR-1976 5.69 3.866e-05 0.0191 0.7968
HSA-MIR-338 5.35 8.893e-05 0.0438 0.7972
HSA-MIR-532 5.35 9.4e-05 0.0462 0.828
HSA-MIR-3909 -5.19 9.448e-05 0.0464 0.7452

Figure S9.  Get High-res Image As an example, this figure shows the association of HSA-MIR-888 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1e-10 with T-test analysis.

Clinical variable #10: 'RADIATIONEXPOSURE'

No miR related to 'RADIATIONEXPOSURE'.

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

RADIATIONEXPOSURE Labels N
  NO 408
  YES 17
     
  Significant markers N = 0
Clinical variable #11: 'EXTRATHYROIDAL.EXTENSION'

76 miRs related to 'EXTRATHYROIDAL.EXTENSION'.

Table S20.  Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION Labels N
  MINIMAL (T3) 126
  MODERATE/ADVANCED (T4A) 16
  NONE 325
  VERY ADVANCED (T4B) 1
     
  Significant markers N = 76
List of top 10 miRs differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

Table S21.  Get Full Table List of top 10 miRs differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

ANOVA_P Q
HSA-MIR-363 1.425e-09 7.32e-07
HSA-MIR-30A 2.205e-09 1.13e-06
HSA-MIR-148B 4.515e-09 2.31e-06
HSA-MIR-126 7.136e-09 3.65e-06
HSA-MIR-758 7.762e-09 3.96e-06
HSA-MIR-21 8.089e-09 4.12e-06
HSA-MIR-376C 9.967e-09 5.06e-06
HSA-MIR-411 1.021e-08 5.18e-06
HSA-MIR-493 1.051e-08 5.32e-06
HSA-MIR-1180 1.439e-08 7.27e-06

Figure S10.  Get High-res Image As an example, this figure shows the association of HSA-MIR-363 to 'EXTRATHYROIDAL.EXTENSION'. P value = 1.42e-09 with ANOVA analysis.

Clinical variable #12: 'COMPLETENESS.OF.RESECTION'

One miR related to 'COMPLETENESS.OF.RESECTION'.

Table S22.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 372
  R1 49
  R2 4
  RX 29
     
  Significant markers N = 1
List of one miR differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S23.  Get Full Table List of one miR differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
HSA-MIR-139 1.238e-05 0.00636

Figure S11.  Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'COMPLETENESS.OF.RESECTION'. P value = 1.24e-05 with ANOVA analysis.

Clinical variable #13: 'NUMBER.OF.LYMPH.NODES'

60 miRs related to 'NUMBER.OF.LYMPH.NODES'.

Table S24.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 3.53 (6.2)
  Significant markers N = 60
  pos. correlated 36
  neg. correlated 24
List of top 10 miRs significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S25.  Get Full Table List of top 10 miRs significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-7-2 -0.3214 2.065e-10 1.06e-07
HSA-MIR-1179 -0.3003 7.496e-09 3.85e-06
HSA-MIR-21 0.2867 1.015e-08 5.19e-06
HSA-MIR-511-2 0.2813 2.041e-08 1.04e-05
HSA-MIR-382 0.2806 5.161e-08 2.63e-05
HSA-MIR-30E -0.2729 5.312e-08 2.7e-05
HSA-MIR-199A-1 0.2713 6.408e-08 3.26e-05
HSA-MIR-874 -0.2711 6.503e-08 3.3e-05
HSA-MIR-31 0.2698 8.183e-08 4.14e-05
HSA-MIR-199A-2 0.2683 9.042e-08 4.57e-05

Figure S12.  Get High-res Image As an example, this figure shows the association of HSA-MIR-7-2 to 'NUMBER.OF.LYMPH.NODES'. P value = 2.07e-10 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #14: 'MULTIFOCALITY'

One miR related to 'MULTIFOCALITY'.

Table S26.  Basic characteristics of clinical feature: 'MULTIFOCALITY'

MULTIFOCALITY Labels N
  MULTIFOCAL 219
  UNIFOCAL 256
     
  Significant markers N = 1
  Higher in UNIFOCAL 0
  Higher in MULTIFOCAL 1
List of one miR differentially expressed by 'MULTIFOCALITY'

Table S27.  Get Full Table List of one miR differentially expressed by 'MULTIFOCALITY'

T(pos if higher in 'UNIFOCAL') ttestP Q AUC
HSA-MIR-132 -3.98 7.994e-05 0.0411 0.6067

Figure S13.  Get High-res Image As an example, this figure shows the association of HSA-MIR-132 to 'MULTIFOCALITY'. P value = 7.99e-05 with T-test analysis.

Clinical variable #15: 'TUMOR.SIZE'

2 miRs related to 'TUMOR.SIZE'.

Table S28.  Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE Mean (SD) 2.95 (1.6)
  Significant markers N = 2
  pos. correlated 0
  neg. correlated 2
List of 2 miRs significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

Table S29.  Get Full Table List of 2 miRs significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-9-2 -0.2032 5.775e-05 0.0297
HSA-MIR-9-1 -0.1996 7.828e-05 0.0402

Figure S14.  Get High-res Image As an example, this figure shows the association of HSA-MIR-9-2 to 'TUMOR.SIZE'. P value = 5.78e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

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

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

  • Number of patients = 485

  • Number of miRs = 514

  • Number of clinical features = 15

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

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[5] 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)
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