PANCANCER subset with 8 initial disease types: Correlation between mRNA expression and clinical features
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)
Overview
Introduction

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

Summary

Testing the association between 17814 genes and 12 clinical features across 1569 samples, statistically thresholded by Q value < 0.05, 12 clinical features related to at least one genes.

- 3027 genes correlated to 'Time to Death'.

- KLHL14 , ASS1 , IGSF11 , UPK1B , C4ORF32 , ...

- 3544 genes correlated to 'AGE'.

- GREB1 , DUOX2 , COL18A1 , GALNTL1 , LDOC1 , ...

- 17276 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

- KLHL14 , ZG16 , SLC22A2 , FOXE1 , PDZD3 , ...

- 9002 genes correlated to 'GENDER'.

- ESR1 , DDX3Y , RSPO1 , RPS4Y1 , EIF1AY , ...

- 274 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

- PPP1R9A , VASN , INSIG2 , PCYT1A , TLE1 , ...

- 16527 genes correlated to 'HISTOLOGICAL.TYPE'.

- KLHL14 , EMX2 , NPR1 , FUT4 , FXYD2 , ...

- 5428 genes correlated to 'PATHOLOGY.T'.

- NOXO1 , CDCA7 , C20ORF151 , B3GNT3 , C13ORF3 , ...

- 12 genes correlated to 'PATHOLOGY.N'.

- FAM73A , TNFRSF10C , MGC50559 , GABARAP , MMP11 , ...

- 33 genes correlated to 'PATHOLOGICSPREAD(M)'.

- KCNC2 , TCF7 , HCN1 , C8ORF30A , NPAS2 , ...

- 7068 genes correlated to 'TUMOR.STAGE'.

- FGF18 , WT1 , UGT1A6 , ZNF503 , KITLG , ...

- 5808 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- CYP3A5 , TCF21 , CYP3A4 , CYP3A7 , AADAC , ...

- 7886 genes correlated to 'NEOADJUVANT.THERAPY'.

- ATP6V1B1 , NPAS3 , UGT1A6 , SCARA3 , GPX2 , ...

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 genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature | Statistical test | Significant genes | Associated with |  | Associated with |
--- | --- | --- | --- | --- | --- | ---
Time to Death | Cox regression test | N=3027 | shorter survival | N=1360 | longer survival | N=1667
AGE | Spearman correlation test | N=3544 | older | N=1692 | younger | N=1852
PRIMARY SITE OF DISEASE | ANOVA test | N=17276 |  |  |  |
GENDER | t test | N=9002 | male | N=4105 | female | N=4897
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=274 | higher score | N=164 | lower score | N=110
HISTOLOGICAL TYPE | ANOVA test | N=16527 |  |  |  |
PATHOLOGY T | Spearman correlation test | N=5428 | higher pT | N=2925 | lower pT | N=2503
PATHOLOGY N | Spearman correlation test | N=12 | higher pN | N=4 | lower pN | N=8
PATHOLOGICSPREAD(M) | ANOVA test | N=33 |  |  |  |
TUMOR STAGE | Spearman correlation test | N=7068 | higher stage | N=3772 | lower stage | N=3296
RADIATIONS RADIATION REGIMENINDICATION | t test | N=5808 | yes | N=2873 | no | N=2935
NEOADJUVANT THERAPY | t test | N=7886 | yes | N=4017 | no | N=3869

Clinical variable #1: 'Time to Death'

3027 genes related to 'Time to Death'.

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

Time to Death | Duration (Months) | 0.1-223.4 (median=23.1)
| censored | N = 978
| death | N = 435
| Significant markers | N = 3027
| associated with shorter survival | 1360
| associated with longer survival | 1667

List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

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

| HazardRatio | Wald_P | Q | C_index
--- | --- | --- | --- | ---
KLHL14 | 1.27 | 0 | 0 | 0.602
ASS1 | 1.32 | 0 | 0 | 0.622
IGSF11 | 1.36 | 0 | 0 | 0.641
UPK1B | 1.22 | 0 | 0 | 0.637
C4ORF32 | 0.77 | 0 | 0 | 0.38
ZRSR1 | 0.54 | 0 | 0 | 0.348
MDS1 | 1.37 | 0 | 0 | 0.619
GALNT12 | 1.32 | 0 | 0 | 0.617
MUC4 | 1.22 | 0 | 0 | 0.637
NUBP1 | 0.47 | 0 | 0 | 0.353

Figure S1. Get High-res Image As an example, this figure shows the association of KLHL14 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 0 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

3544 genes related to 'AGE'.

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

AGE | Mean (SD) | 61.27 (13)
| Significant markers | N = 3544
| pos. correlated | 1692
| neg. correlated | 1852

List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

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

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
GREB1 | -0.2885 | 3.417e-31 | 6.09e-27
DUOX2 | 0.2737 | 4.023e-28 | 7.17e-24
COL18A1 | -0.2709 | 1.487e-27 | 2.65e-23
GALNTL1 | -0.2655 | 1.69e-26 | 3.01e-22
LDOC1 | -0.2641 | 3.213e-26 | 5.72e-22
CYP2C18 | 0.261 | 1.219e-25 | 2.17e-21
SYT12 | -0.2608 | 1.374e-25 | 2.45e-21
OBSL1 | -0.2581 | 4.382e-25 | 7.8e-21
SH3BP5 | -0.258 | 4.545e-25 | 8.09e-21
BBOX1 | -0.2564 | 9.031e-25 | 1.61e-20

Figure S2. Get High-res Image As an example, this figure shows the association of GREB1 to 'AGE'. P value = 3.42e-31 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

17276 genes related to 'PRIMARY.SITE.OF.DISEASE'.

Table S5. Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE | Labels | N
| BREAST | 529
| COLON | 154
| ENDOMETRIAL | 54
| KIDNEY | 72
| LUNG | 154
| OMENTUM | 2
| OVARY | 532
| PERITONEUM (OVARY) | 2
| RECTUM | 68
| Significant markers | N = 17276

List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S6. Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

| ANOVA_P | Q
--- | --- | ---
KLHL14 | 0 | 0
ZG16 | 0 | 0
SLC22A2 | 0 | 0
FOXE1 | 0 | 0
PDZD3 | 0 | 0
EMX2 | 0 | 0
NPR1 | 0 | 0
FUT4 | 0 | 0
ACF | 0 | 0
FXYD2 | 0 | 0

Figure S3. Get High-res Image As an example, this figure shows the association of KLHL14 to 'PRIMARY.SITE.OF.DISEASE'. P value = 0 with ANOVA analysis.

Clinical variable #4: 'GENDER'

9002 genes related to 'GENDER'.

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

GENDER | Labels | N
| FEMALE | 1293
| MALE | 276
| Significant markers | N = 9002
| Higher in MALE | 4105
| Higher in FEMALE | 4897

List of top 10 genes differentially expressed by 'GENDER'

Table S8. Get Full Table List of top 10 genes differentially expressed by 'GENDER'

| T(pos if higher in 'MALE') | ttestP | Q | AUC
--- | --- | --- | --- | ---
ESR1 | -37.57 | 4.305e-174 | 7.67e-170 | 0.8825
DDX3Y | 54.97 | 1.99e-164 | 3.55e-160 | 0.988
RSPO1 | -31.37 | 6.859e-164 | 1.22e-159 | 0.8489
RPS4Y1 | 53.88 | 2.037e-156 | 3.63e-152 | 0.9794
EIF1AY | 50.16 | 1.226e-150 | 2.18e-146 | 0.9879
RPS4Y2 | 49.57 | 1.819e-146 | 3.24e-142 | 0.9867
ERBB4 | -32.64 | 7.076e-145 | 1.26e-140 | 0.8607
JARID1D | 44.65 | 2.215e-144 | 3.94e-140 | 0.9772
SCGB2A2 | -29.3 | 2.86e-142 | 5.09e-138 | 0.8615
CYORF15A | 43.63 | 1.659e-135 | 2.95e-131 | 0.9824

Figure S4. Get High-res Image As an example, this figure shows the association of ESR1 to 'GENDER'. P value = 4.3e-174 with T-test analysis.

Clinical variable #5: 'KARNOFSKY.PERFORMANCE.SCORE'

274 genes related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S9. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 60.55 (34)
| Significant markers | N = 274
| pos. correlated | 164
| neg. correlated | 110

List of top 10 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

Table S10. Get Full Table List of top 10 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
PPP1R9A | 0.6265 | 3.091e-11 | 5.51e-07
VASN | 0.6117 | 1.189e-10 | 2.12e-06
INSIG2 | -0.5926 | 6.1e-10 | 1.09e-05
PCYT1A | -0.5809 | 1.57e-09 | 2.8e-05
TLE1 | 0.5742 | 2.663e-09 | 4.74e-05
MARCH7 | -0.5725 | 3.049e-09 | 5.43e-05
CCDC135 | 0.5661 | 4.96e-09 | 8.83e-05
CXXC5 | 0.5647 | 5.543e-09 | 9.87e-05
ZNF503 | 0.5639 | 5.897e-09 | 0.000105
SOX5 | 0.5596 | 8.108e-09 | 0.000144

Figure S5. Get High-res Image As an example, this figure shows the association of PPP1R9A to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 3.09e-11 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #6: 'HISTOLOGICAL.TYPE'

16527 genes related to 'HISTOLOGICAL.TYPE'.

Table S11. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| COLON ADENOCARCINOMA | 128
| COLON MUCINOUS ADENOCARCINOMA | 24
| ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 41
| KIDNEY CLEAR CELL RENAL CARCINOMA | 72
| LUNG BASALOID SQUAMOUS CELL CARCINOMA | 5
| LUNG PAPILLARY SQUAMOUS CELL CARICNOMA | 1
| LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) | 148
| MIXED SEROUS AND ENDOMETRIOID | 1
| RECTAL ADENOCARCINOMA | 58
| RECTAL MUCINOUS ADENOCARCINOMA | 7
| SEROUS CYSTADENOCARCINOMA | 536
| SEROUS ENDOMETRIAL ADENOCARCINOMA | 12
| Significant markers | N = 16527

List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S12. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

| ANOVA_P | Q
--- | --- | ---
KLHL14 | 0 | 0
EMX2 | 0 | 0
NPR1 | 0 | 0
FUT4 | 0 | 0
FXYD2 | 0 | 0
SPINK4 | 0 | 0
SLC12A2 | 0 | 0
CDH17 | 0 | 0
SATB2 | 0 | 0
OVOL2 | 0 | 0

Figure S6. Get High-res Image As an example, this figure shows the association of KLHL14 to 'HISTOLOGICAL.TYPE'. P value = 0 with ANOVA analysis.

Clinical variable #7: 'PATHOLOGY.T'

5428 genes related to 'PATHOLOGY.T'.

Table S13. Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T | Mean (SD) | 2.35 (0.85)
|  | N
| T1 | 80
| T2 | 160
| T3 | 179
| T4 | 29
| Significant markers | N = 5428
| pos. correlated | 2925
| neg. correlated | 2503

List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S14. Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
NOXO1 | 0.5004 | 9.064e-30 | 1.61e-25
CDCA7 | 0.4999 | 1.052e-29 | 1.87e-25
C20ORF151 | 0.4993 | 1.281e-29 | 2.28e-25
B3GNT3 | 0.4967 | 2.749e-29 | 4.9e-25
C13ORF3 | 0.4934 | 7.329e-29 | 1.31e-24
C19ORF21 | 0.4912 | 1.388e-28 | 2.47e-24
LIFR | -0.491 | 1.488e-28 | 2.65e-24
NR3C1 | -0.4893 | 2.372e-28 | 4.22e-24
MUC13 | 0.4884 | 3.138e-28 | 5.59e-24
TACSTD1 | 0.4866 | 5.24e-28 | 9.33e-24

Figure S7. Get High-res Image As an example, this figure shows the association of NOXO1 to 'PATHOLOGY.T'. P value = 9.06e-30 with Spearman correlation analysis.

Clinical variable #8: 'PATHOLOGY.N'

12 genes related to 'PATHOLOGY.N'.

Table S15. Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N | Mean (SD) | 0.52 (0.77)
|  | N
| N0 | 268
| N1 | 86
| N2 | 57
| N3 | 5
| Significant markers | N = 12
| pos. correlated | 4
| neg. correlated | 8

List of top 10 genes significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

Table S16. Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
FAM73A | -0.2672 | 3.138e-08 | 0.000559
TNFRSF10C | -0.2655 | 3.823e-08 | 0.000681
MGC50559 | -0.264 | 4.611e-08 | 0.000821
GABARAP | -0.2477 | 3.111e-07 | 0.00554
MMP11 | 0.2381 | 8.944e-07 | 0.0159
LUZP2 | 0.2377 | 9.368e-07 | 0.0167
ZNF273 | 0.233 | 1.551e-06 | 0.0276
CNDP2 | -0.2328 | 1.588e-06 | 0.0283
IFIT3 | -0.2294 | 2.261e-06 | 0.0403
BIRC3 | -0.2294 | 2.268e-06 | 0.0404

Figure S8. Get High-res Image As an example, this figure shows the association of FAM73A to 'PATHOLOGY.N'. P value = 3.14e-08 with Spearman correlation analysis.

Clinical variable #9: 'PATHOLOGICSPREAD(M)'

33 genes related to 'PATHOLOGICSPREAD(M)'.

Table S17. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) | Labels | N
| M0 | 399
| M1 | 43
| M1A | 1
| Significant markers | N = 33

List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S18. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

| ANOVA_P | Q
--- | --- | ---
KCNC2 | 1.858e-11 | 3.31e-07
TCF7 | 9.2e-09 | 0.000164
HCN1 | 2.486e-08 | 0.000443
C8ORF30A | 7.085e-08 | 0.00126
NPAS2 | 1.24e-07 | 0.00221
SERPINA4 | 1.444e-07 | 0.00257
PLOD3 | 4.299e-07 | 0.00765
SPACA3 | 4.451e-07 | 0.00793
NIBP | 4.699e-07 | 0.00837
F10 | 8.055e-07 | 0.0143

Figure S9. Get High-res Image As an example, this figure shows the association of KCNC2 to 'PATHOLOGICSPREAD(M)'. P value = 1.86e-11 with ANOVA analysis.

Clinical variable #10: 'TUMOR.STAGE'

7068 genes related to 'TUMOR.STAGE'.

Table S19. Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE | Mean (SD) | 2.58 (0.93)
|  | N
| Stage 1 | 183
| Stage 2 | 160
| Stage 3 | 512
| Stage 4 | 119
| Significant markers | N = 7068
| pos. correlated | 3772
| neg. correlated | 3296

List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S20. Get Full Table List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
FGF18 | 0.5153 | 3.592e-67 | 6.4e-63
WT1 | 0.4972 | 6.068e-62 | 1.08e-57
UGT1A6 | -0.4794 | 4.111e-57 | 7.32e-53
ZNF503 | 0.4768 | 1.932e-56 | 3.44e-52
KITLG | -0.4722 | 3.069e-55 | 5.47e-51
DOK7 | 0.4718 | 3.919e-55 | 6.98e-51
SOCS2 | -0.4711 | 5.78e-55 | 1.03e-50
RIMS4 | 0.471 | 6.333e-55 | 1.13e-50
DNASE1L3 | -0.4708 | 7.054e-55 | 1.26e-50
RBM38 | 0.4703 | 9.45e-55 | 1.68e-50

Figure S10. Get High-res Image As an example, this figure shows the association of FGF18 to 'TUMOR.STAGE'. P value = 3.59e-67 with Spearman correlation analysis.

Clinical variable #11: 'RADIATIONS.RADIATION.REGIMENINDICATION'

5808 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S21. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 178
| YES | 1391
| Significant markers | N = 5808
| Higher in YES | 2873
| Higher in NO | 2935

List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S22. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
CYP3A5 | 22.57 | 1.156e-79 | 2.06e-75 | 0.7893
TCF21 | 21.82 | 1.425e-70 | 2.54e-66 | 0.7935
CYP3A4 | 20.46 | 2.734e-69 | 4.87e-65 | 0.7745
CYP3A7 | 20.52 | 3.27e-69 | 5.82e-65 | 0.7648
AADAC | 20.33 | 8.409e-65 | 1.5e-60 | 0.7731
MAP2K7 | 21.2 | 1.802e-64 | 3.21e-60 | 0.8071
CCDC71 | 21.42 | 6.771e-64 | 1.21e-59 | 0.8175
REG1A | 19.5 | 4.283e-61 | 7.63e-57 | 0.7759
PDZD3 | 17.28 | 1.942e-58 | 3.46e-54 | 0.6873
CHMP4B | 19.98 | 1.429e-57 | 2.54e-53 | 0.8079

Figure S11. Get High-res Image As an example, this figure shows the association of CYP3A5 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.16e-79 with T-test analysis.

Clinical variable #12: 'NEOADJUVANT.THERAPY'

7886 genes related to 'NEOADJUVANT.THERAPY'.

Table S23. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'

NEOADJUVANT.THERAPY | Labels | N
| NO | 690
| YES | 879
| Significant markers | N = 7886
| Higher in YES | 4017
| Higher in NO | 3869

List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

Table S24. Get Full Table List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
ATP6V1B1 | -21.83 | 5.409e-92 | 9.63e-88 | 0.7813
NPAS3 | -21.63 | 8.136e-90 | 1.45e-85 | 0.7879
UGT1A6 | 21.58 | 2.396e-88 | 4.27e-84 | 0.7335
SCARA3 | -21.3 | 2.065e-87 | 3.68e-83 | 0.7803
GPX2 | 21.34 | 3.912e-86 | 6.97e-82 | 0.7297
PEA15 | -20.89 | 2.634e-85 | 4.69e-81 | 0.777
SLC27A6 | -20.73 | 9.426e-84 | 1.68e-79 | 0.7782
ZNF667 | -20.61 | 1.379e-83 | 2.46e-79 | 0.7671
NPR1 | -20.83 | 1.871e-83 | 3.33e-79 | 0.7744
KLHL14 | -20.77 | 7.636e-83 | 1.36e-78 | 0.7503

Figure S12. Get High-res Image As an example, this figure shows the association of ATP6V1B1 to 'NEOADJUVANT.THERAPY'. P value = 5.41e-92 with T-test analysis.

Methods & Data
Input

- Expresson data file = PANCAN8.medianexp.txt

- Clinical data file = PANCAN8.clin.merged.picked.txt

- Number of patients = 1569

- Number of genes = 17814

- Number of clinical features = 12

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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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