Correlation between miRseq expression and clinical features
Thyroid Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1BV7F35
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/C1BV7F35
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 483 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

  • 4 miRs correlated to 'AGE'.

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

  • 38 miRs correlated to 'NEOPLASM.DISEASESTAGE'.

    • HSA-MIR-139 ,  HSA-MIR-210 ,  HSA-MIR-146B ,  HSA-MIR-425 ,  HSA-MIR-31 ,  ...

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

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

  • 65 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-655

  • 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 ,  ...

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

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

  • 71 miRs correlated to 'EXTRATHYROIDAL.EXTENSION'.

    • HSA-MIR-30A ,  HSA-MIR-363 ,  HSA-MIR-148B ,  HSA-MIR-126 ,  HSA-MIR-21 ,  ...

  • 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

  • 3 miRs correlated to 'TUMOR.SIZE'.

    • HSA-MIR-9-2 ,  HSA-MIR-9-1 ,  HSA-MIR-183

  • 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=4 older N=2 younger N=2
NEOPLASM DISEASESTAGE ANOVA test N=38        
PATHOLOGY T STAGE Spearman correlation test N=15 higher stage N=3 lower stage N=12
PATHOLOGY N STAGE t test N=65 class1 N=32 class0 N=33
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=11 yes N=8 no N=3
RADIATIONEXPOSURE t test   N=0        
EXTRATHYROIDAL EXTENSION ANOVA test N=71        
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=3 higher tumor.size N=1 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=14.9)
  censored N = 464
  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 2.175e-05 0.011 0.885
HSA-MIR-181A-2 0.33 3.884e-05 0.02 0.176
HSA-MIR-487A 2.6 4.319e-05 0.022 0.843
HSA-MIR-425 5.6 7.624e-05 0.039 0.79
HSA-MIR-30D 0.14 8.088e-05 0.041 0.16

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 = 2.17e-05 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

4 miRs related to 'AGE'.

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

AGE Mean (SD) 47.22 (16)
  Significant markers N = 4
  pos. correlated 2
  neg. correlated 2
List of 4 miRs significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of 4 miRs significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-625 -0.197 1.296e-05 0.00666
HSA-MIR-376A-1 0.2586 1.408e-05 0.00722
HSA-MIR-181A-2 -0.1925 2.057e-05 0.0105
HSA-MIR-1229 0.1996 6.359e-05 0.0325

Figure S2.  Get High-res Image As an example, this figure shows the association of HSA-MIR-625 to 'AGE'. P value = 1.3e-05 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

38 miRs related to 'NEOPLASM.DISEASESTAGE'.

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

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 273
  STAGE II 51
  STAGE III 106
  STAGE IV 2
  STAGE IVA 43
  STAGE IVC 6
     
  Significant markers N = 38
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 7.912e-13 4.07e-10
HSA-MIR-210 1.394e-10 7.15e-08
HSA-MIR-146B 1.887e-07 9.66e-05
HSA-MIR-425 2.491e-07 0.000127
HSA-MIR-31 4.179e-07 0.000213
HSA-MIR-126 5.388e-07 0.000274
HSA-MIR-154 7.694e-07 0.000391
HSA-MIR-376C 1.078e-06 0.000547
HSA-MIR-369 1.739e-06 0.00088
HSA-MIR-655 1.906e-06 0.000963

Figure S3.  Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'NEOPLASM.DISEASESTAGE'. P value = 7.91e-13 with ANOVA analysis.

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

15 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
  2 161
  3 159
  4 21
     
  Significant markers N = 15
  pos. correlated 3
  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 -0.2822 2.962e-10 1.52e-07
HSA-MIR-126 -0.2693 1.952e-09 1e-06
HSA-MIR-363 -0.2412 8.753e-08 4.48e-05
HSA-MIR-3074 -0.2045 6.133e-06 0.00313
HSA-MIR-30C-2 -0.2036 6.754e-06 0.00344
HSA-MIR-92B 0.2008 9.116e-06 0.00464
HSA-MIR-145 -0.1992 1.076e-05 0.00547
HSA-MIR-7-2 -0.2008 1.179e-05 0.00598
HSA-MIR-20B -0.1973 1.337e-05 0.00677
HSA-MIR-433 0.2412 2.274e-05 0.0115

Figure S4.  Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'PATHOLOGY.T.STAGE'. P value = 2.96e-10 with Spearman correlation analysis.

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

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

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

PATHOLOGY.N.STAGE Labels N
  class0 220
  class1 216
     
  Significant markers N = 65
  Higher in class1 32
  Higher in class0 33
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 7.72 1.25e-13 6.42e-11 0.6736
HSA-MIR-21 7.52 3.688e-13 1.89e-10 0.6811
HSA-MIR-204 -7.02 9.13e-12 4.67e-09 0.6756
HSA-MIR-7-2 -6.98 1.174e-11 6e-09 0.6834
HSA-MIR-1179 -6.85 2.786e-11 1.42e-08 0.6825
HSA-MIR-222 6.74 6.751e-11 3.44e-08 0.6556
HSA-MIR-511-2 6.35 5.319e-10 2.7e-07 0.6681
HSA-MIR-221 6.23 1.371e-09 6.95e-07 0.6343
HSA-MIR-375 6.08 2.993e-09 1.51e-06 0.637
HSA-MIR-3074 -6.03 3.669e-09 1.85e-06 0.6615

Figure S5.  Get High-res Image As an example, this figure shows the association of HSA-MIR-146B to 'PATHOLOGY.N.STAGE'. P value = 1.25e-13 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 264
  M1 9
  MX 209
     
  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 4.996e-06 0.00257
HSA-MIR-589 3.046e-05 0.0156
HSA-MIR-655 6.792e-05 0.0348

Figure S6.  Get High-res Image As an example, this figure shows the association of HSA-MIR-3677 to 'PATHOLOGY.M.STAGE'. P value = 5e-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 354
  MALE 129
     
  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 -5.2 4.795e-07 0.000246 0.6551
HSA-MIR-361 -4.42 1.406e-05 0.00721 0.617

Figure S7.  Get High-res Image As an example, this figure shows the association of HSA-MIR-651 to 'GENDER'. P value = 4.79e-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 340
  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 8.373e-41 4.3e-38
HSA-MIR-146B 7.771e-33 3.99e-30
HSA-MIR-7-2 1.34e-24 6.86e-22
HSA-MIR-204 9.277e-22 4.74e-19
HSA-MIR-375 3.517e-21 1.79e-18
HSA-MIR-1179 4.212e-21 2.14e-18
HSA-MIR-345 6.079e-21 3.09e-18
HSA-MIR-31 1.343e-20 6.81e-18
HSA-MIR-511-2 1.418e-20 7.17e-18
HSA-MIR-511-1 6.591e-20 3.33e-17

Figure S8.  Get High-res Image As an example, this figure shows the association of HSA-MIR-21 to 'HISTOLOGICAL.TYPE'. P value = 8.37e-41 with ANOVA analysis.

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

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

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

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 14
  YES 469
     
  Significant markers N = 11
  Higher in YES 8
  Higher in NO 3
List of top 10 miRs differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

T(pos if higher in 'YES') ttestP Q AUC
HSA-MIR-888 9.75 1.006e-10 5.03e-08 0.885
HSA-MIR-374A -8.75 2.656e-07 0.000133 0.9175
HSA-MIR-660 7.95 9.216e-07 0.000459 0.8862
HSA-MIR-324 6.56 8.752e-06 0.00435 0.8451
HSA-MIR-20B 6.36 1.377e-05 0.00683 0.8393
HSA-MIR-3130-1 -5.51 3.7e-05 0.0183 0.7428
HSA-MIR-1976 5.69 3.895e-05 0.0192 0.7968
HSA-MIR-338 5.36 8.605e-05 0.0424 0.7979
HSA-MIR-3909 -5.21 9.124e-05 0.0449 0.7457
HSA-MIR-532 5.36 9.213e-05 0.0452 0.8293

Figure S9.  Get High-res Image As an example, this figure shows the association of HSA-MIR-888 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.01e-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 407
  YES 17
     
  Significant markers N = 0
Clinical variable #11: 'EXTRATHYROIDAL.EXTENSION'

71 miRs related to 'EXTRATHYROIDAL.EXTENSION'.

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

EXTRATHYROIDAL.EXTENSION Labels N
  MINIMAL (T3) 125
  MODERATE/ADVANCED (T4A) 16
  NONE 324
  VERY ADVANCED (T4B) 1
     
  Significant markers N = 71
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-30A 3.319e-09 1.71e-06
HSA-MIR-363 3.35e-09 1.72e-06
HSA-MIR-148B 8.793e-09 4.5e-06
HSA-MIR-126 1.312e-08 6.7e-06
HSA-MIR-21 1.313e-08 6.7e-06
HSA-MIR-758 1.7e-08 8.65e-06
HSA-MIR-411 1.921e-08 9.76e-06
HSA-MIR-376C 2.017e-08 1.02e-05
HSA-MIR-1180 2.032e-08 1.03e-05
HSA-MIR-493 2.456e-08 1.24e-05

Figure S10.  Get High-res Image As an example, this figure shows the association of HSA-MIR-30A to 'EXTRATHYROIDAL.EXTENSION'. P value = 3.32e-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 47
  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 1.471e-05 0.00756

Figure S11.  Get High-res Image As an example, this figure shows the association of HSA-MIR-139 to 'COMPLETENESS.OF.RESECTION'. P value = 1.47e-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) 3.54 (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 -0.3175 3.888e-10 2e-07
HSA-MIR-1179 -0.2956 1.431e-08 7.34e-06
HSA-MIR-21 0.2833 1.687e-08 8.64e-06
HSA-MIR-511-2 0.2778 3.362e-08 1.72e-05
HSA-MIR-382 0.2768 8.688e-08 4.43e-05
HSA-MIR-30E -0.2685 9.506e-08 4.84e-05
HSA-MIR-199A-1 0.2674 1.083e-07 5.5e-05
HSA-MIR-874 -0.2665 1.198e-07 6.07e-05
HSA-MIR-31 0.2662 1.329e-07 6.72e-05
HSA-MIR-134 0.2649 1.539e-07 7.77e-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 = 3.89e-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 218
  UNIFOCAL 255
     
  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 -3.94 9.575e-05 0.0492 0.6054

Figure S13.  Get High-res Image As an example, this figure shows the association of HSA-MIR-132 to 'MULTIFOCALITY'. P value = 9.58e-05 with T-test analysis.

Clinical variable #15: 'TUMOR.SIZE'

3 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 = 3
  pos. correlated 1
  neg. correlated 2
List of 3 miRs significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

Table S29.  Get Full Table List of 3 miRs significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

SpearmanCorr corrP Q
HSA-MIR-9-2 -0.2071 4.34e-05 0.0223
HSA-MIR-9-1 -0.2035 5.891e-05 0.0302
HSA-MIR-183 0.1976 9.702e-05 0.0497

Figure S14.  Get High-res Image As an example, this figure shows the association of HSA-MIR-9-2 to 'TUMOR.SIZE'. P value = 4.34e-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 = 483

  • 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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