PANCANCER: 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 1644 samples, statistically thresholded by Q value < 0.05, 12 clinical features related to at least one genes.

- 2929 genes correlated to 'Time to Death'.

- KLHL14 , ASS1 , UPK1B , C4ORF32 , ZRSR1 , ...

- 4218 genes correlated to 'AGE'.

- DUOX2 , GALNTL1 , GREB1 , BBOX1 , BACE1 , ...

- 17488 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

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

- 8361 genes correlated to 'GENDER'.

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

- 1127 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

- PPP1R9A , SMARCC2 , MGRN1 , IL8 , PEA15 , ...

- 17230 genes correlated to 'HISTOLOGICAL.TYPE'.

- KLHL14 , PDZD3 , EMX2 , NPR1 , FUT4 , ...

- 6063 genes correlated to 'PATHOLOGY.T'.

- C13ORF3 , CDCA7 , LIFR , NR3C1 , PDSS1 , ...

- 11 genes correlated to 'PATHOLOGY.N'.

- TNFRSF10C , FAM73A , ZNF273 , GABARAP , MGC50559 , ...

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

- KCNC2 , TCF7 , HCN1 , C8ORF30A , SPACA3 , ...

- 7375 genes correlated to 'TUMOR.STAGE'.

- FGF18 , WT1 , KITLG , RBM38 , ELL2 , ...

- 5965 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

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

- 7746 genes correlated to 'NEOADJUVANT.THERAPY'.

- UGT1A6 , ATP6V1B1 , NPAS3 , 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=2929 | shorter survival | N=1326 | longer survival | N=1603
AGE | Spearman correlation test | N=4218 | older | N=2062 | younger | N=2156
PRIMARY SITE OF DISEASE | ANOVA test | N=17488 |  |  |  |
GENDER | t test | N=8361 | male | N=3797 | female | N=4564
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=1127 | higher score | N=603 | lower score | N=524
HISTOLOGICAL TYPE | ANOVA test | N=17230 |  |  |  |
PATHOLOGY T | Spearman correlation test | N=6063 | higher pT | N=3246 | lower pT | N=2817
PATHOLOGY N | Spearman correlation test | N=11 | higher pN | N=3 | lower pN | N=8
PATHOLOGICSPREAD(M) | ANOVA test | N=32 |  |  |  |
TUMOR STAGE | Spearman correlation test | N=7375 | higher stage | N=3977 | lower stage | N=3398
RADIATIONS RADIATION REGIMENINDICATION | t test | N=5965 | yes | N=2978 | no | N=2987
NEOADJUVANT THERAPY | t test | N=7746 | yes | N=3927 | no | N=3819

Clinical variable #1: 'Time to Death'

2929 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)
| censored | N = 1037
| death | N = 450
| Significant markers | N = 2929
| associated with shorter survival | 1326
| associated with longer survival | 1603

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 | 1.26 | 0 | 0 | 0.603
ASS1 | 1.3 | 0 | 0 | 0.624
UPK1B | 1.21 | 0 | 0 | 0.637
C4ORF32 | 0.78 | 0 | 0 | 0.388
ZRSR1 | 0.57 | 0 | 0 | 0.347
MDS1 | 1.36 | 0 | 0 | 0.624
GALNT12 | 1.3 | 0 | 0 | 0.618
MUC4 | 1.22 | 0 | 0 | 0.636
NUBP1 | 0.47 | 0 | 0 | 0.352
BTG3 | 1.44 | 0 | 0 | 0.641

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'

4218 genes related to 'AGE'.

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

AGE | Mean (SD) | 60.95 (13)
| Significant markers | N = 4218
| pos. correlated | 2062
| neg. correlated | 2156

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
--- | --- | --- | ---
DUOX2 | 0.2913 | 3.291e-33 | 5.86e-29
GALNTL1 | -0.2894 | 8.769e-33 | 1.56e-28
GREB1 | -0.2814 | 5.243e-31 | 9.34e-27
BBOX1 | -0.2811 | 5.918e-31 | 1.05e-26
BACE1 | -0.2811 | 6.153e-31 | 1.1e-26
OBSL1 | -0.2801 | 1.015e-30 | 1.81e-26
ADORA1 | -0.2732 | 2.986e-29 | 5.32e-25
KRTAP4-10 | 0.2708 | 9.306e-29 | 1.66e-24
LDOC1 | -0.2703 | 1.193e-28 | 2.12e-24
DUOXA2 | 0.2658 | 9.8e-28 | 1.74e-23

Figure S2. Get High-res Image As an example, this figure shows the association of DUOX2 to 'AGE'. P value = 3.29e-33 with Spearman correlation analysis. The straight line presents the best linear regression.

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

17488 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
| CENTRAL NERVOUS SYSTEM | 27
| COLON | 154
| ENDOMETRIAL | 54
| KIDNEY | 88
| LUNG | 186
| OMENTUM | 2
| OVARY | 532
| PERITONEUM (OVARY) | 2
| RECTUM | 68
| Significant markers | N = 17488

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
ASS1 | 0 | 0
FUT4 | 0 | 0
ACF | 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'

8361 genes related to 'GENDER'.

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

GENDER | Labels | N
| FEMALE | 1324
| MALE | 320
| Significant markers | N = 8361
| Higher in MALE | 3797
| Higher in FEMALE | 4564

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 | -37.46 | 2.422e-186 | 4.32e-182 | 0.8753
DDX3Y | 56.06 | 4.785e-184 | 8.52e-180 | 0.9837
RPS4Y1 | 55.35 | 1.517e-176 | 2.7e-172 | 0.9729
RSPO1 | -31.9 | 8.985e-172 | 1.6e-167 | 0.8487
EIF1AY | 51.16 | 2.511e-168 | 4.47e-164 | 0.984
RPS4Y2 | 51.24 | 8.607e-166 | 1.53e-161 | 0.9817
JARID1D | 46.69 | 4.939e-165 | 8.79e-161 | 0.975
SCGB2A2 | -30.29 | 2.228e-156 | 3.97e-152 | 0.8543
CYORF15A | 45.74 | 9.521e-156 | 1.7e-151 | 0.9805
SCGB1D2 | -30.44 | 2.073e-127 | 3.69e-123 | 0.862

Figure S4. Get High-res Image As an example, this figure shows the association of ESR1 to 'GENDER'. P value = 2.42e-186 with T-test analysis.

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

1127 genes related to 'KARNOFSKY.PERFORMANCE.SCORE'.

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

KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 64.2 (34)
| Significant markers | N = 1127
| pos. correlated | 603
| neg. correlated | 524

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 | 0.6219 | 2.519e-13 | 4.49e-09
SMARCC2 | 0.6074 | 1.245e-12 | 2.22e-08
MGRN1 | 0.6059 | 1.462e-12 | 2.6e-08
IL8 | -0.603 | 1.995e-12 | 3.55e-08
PEA15 | 0.6005 | 2.582e-12 | 4.6e-08
RNF40 | 0.5999 | 2.76e-12 | 4.91e-08
SDC1 | -0.5987 | 3.122e-12 | 5.56e-08
TTYH1 | 0.5985 | 3.184e-12 | 5.67e-08
CORO2B | 0.5983 | 3.254e-12 | 5.79e-08
LGALS8 | -0.5979 | 3.394e-12 | 6.04e-08

Figure S5. Get High-res Image As an example, this figure shows the association of PPP1R9A to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 2.52e-13 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #6: 'HISTOLOGICAL.TYPE'

17230 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE | Labels | N
| ASTROCYTOMA | 10
| COLON ADENOCARCINOMA | 128
| COLON MUCINOUS ADENOCARCINOMA | 24
| ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 41
| KIDNEY CLEAR CELL RENAL CARCINOMA | 72
| KIDNEY PAPILLARY RENAL CELL CARCINOMA | 16
| LUNG ADENOCARCINOMA MIXED SUBTYPE | 1
| LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) | 30
| LUNG BASALOID SQUAMOUS CELL CARCINOMA | 5
| LUNG CLEAR CELL ADENOCARCINOMA | 1
| LUNG PAPILLARY SQUAMOUS CELL CARICNOMA | 1
| LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) | 148
| MIXED SEROUS AND ENDOMETRIOID | 1
| OLIGOASTROCYTOMA | 9
| OLIGODENDROGLIOMA | 8
| RECTAL ADENOCARCINOMA | 58
| RECTAL MUCINOUS ADENOCARCINOMA | 7
| SEROUS CYSTADENOCARCINOMA | 536
| SEROUS ENDOMETRIAL ADENOCARCINOMA | 12
| Significant markers | N = 17230

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
PDZD3 | 0 | 0
EMX2 | 0 | 0
NPR1 | 0 | 0
FUT4 | 0 | 0
FXYD2 | 0 | 0
CLDN3 | 0 | 0
SPINK4 | 0 | 0
SFTPC | 0 | 0
SLC12A2 | 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'

6063 genes related to 'PATHOLOGY.T'.

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

PATHOLOGY.T | Mean (SD) | 2.28 (0.85)
|  | N
| T1 | 99
| T2 | 186
| T3 | 182
| T4 | 29
| Significant markers | N = 6063
| pos. correlated | 3246
| neg. correlated | 2817

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
--- | --- | --- | ---
C13ORF3 | 0.5362 | 2.934e-38 | 5.23e-34
CDCA7 | 0.525 | 1.745e-36 | 3.11e-32
LIFR | -0.5247 | 1.959e-36 | 3.49e-32
NR3C1 | -0.5182 | 1.991e-35 | 3.55e-31
PDSS1 | 0.5137 | 9.432e-35 | 1.68e-30
NOXO1 | 0.5123 | 1.561e-34 | 2.78e-30
MAL | -0.509 | 4.748e-34 | 8.45e-30
C20ORF151 | 0.5069 | 9.891e-34 | 1.76e-29
C20ORF42 | 0.5054 | 1.641e-33 | 2.92e-29
ADHFE1 | -0.505 | 1.837e-33 | 3.27e-29

Figure S7. Get High-res Image As an example, this figure shows the association of C13ORF3 to 'PATHOLOGY.T'. P value = 2.93e-38 with Spearman correlation analysis.

Clinical variable #8: 'PATHOLOGY.N'

11 genes related to 'PATHOLOGY.N'.

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

PATHOLOGY.N | Mean (SD) | 0.51 (0.77)
|  | N
| N0 | 291
| N1 | 92
| N2 | 61
| N3 | 5
| Significant markers | N = 11
| pos. correlated | 3
| 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
--- | --- | --- | ---
TNFRSF10C | -0.2625 | 1.633e-08 | 0.000291
FAM73A | -0.2567 | 3.455e-08 | 0.000616
ZNF273 | 0.2506 | 7.399e-08 | 0.00132
GABARAP | -0.2445 | 1.558e-07 | 0.00277
MGC50559 | -0.2441 | 1.635e-07 | 0.00291
LUZP2 | 0.2375 | 3.786e-07 | 0.00674
RASD1 | -0.2271 | 1.165e-06 | 0.0207
IFIT3 | -0.2242 | 1.598e-06 | 0.0285
CNDP2 | -0.2221 | 2.001e-06 | 0.0356
DHCR7 | 0.2215 | 2.148e-06 | 0.0382

Figure S8. Get High-res Image As an example, this figure shows the association of TNFRSF10C to 'PATHOLOGY.N'. P value = 1.63e-08 with Spearman correlation analysis.

Clinical variable #9: 'PATHOLOGICSPREAD(M)'

32 genes related to 'PATHOLOGICSPREAD(M)'.

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

PATHOLOGICSPREAD(M) | Labels | N
| M0 | 438
| M1 | 46
| M1A | 1
| Significant markers | N = 32

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 | 9.882e-10 | 1.76e-05
TCF7 | 1.647e-08 | 0.000293
HCN1 | 1.791e-08 | 0.000319
C8ORF30A | 9.153e-08 | 0.00163
SPACA3 | 1.758e-07 | 0.00313
F10 | 2.716e-07 | 0.00484
SERPINA4 | 4.041e-07 | 0.0072
FGFR4 | 4.465e-07 | 0.00795
ACSL6 | 5.06e-07 | 0.00901
NPAS2 | 5.501e-07 | 0.00979

Figure S9. Get High-res Image As an example, this figure shows the association of KCNC2 to 'PATHOLOGICSPREAD(M)'. P value = 9.88e-10 with ANOVA analysis.

Clinical variable #10: 'TUMOR.STAGE'

7375 genes related to 'TUMOR.STAGE'.

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

TUMOR.STAGE | Mean (SD) | 2.54 (0.95)
|  | N
| Stage 1 | 211
| Stage 2 | 166
| Stage 3 | 516
| Stage 4 | 122
| Significant markers | N = 7375
| pos. correlated | 3977
| neg. correlated | 3398

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 | 0.5216 | 6.885e-72 | 1.23e-67
WT1 | 0.5086 | 7.189e-68 | 1.28e-63
KITLG | -0.4934 | 2.13e-63 | 3.79e-59
RBM38 | 0.4894 | 2.993e-62 | 5.33e-58
ELL2 | -0.4844 | 7.667e-61 | 1.37e-56
KLK6 | 0.4818 | 3.978e-60 | 7.08e-56
KLK8 | 0.4816 | 4.669e-60 | 8.31e-56
ZNF503 | 0.4796 | 1.666e-59 | 2.97e-55
RIMS4 | 0.4784 | 3.455e-59 | 6.15e-55
DOK7 | 0.4783 | 3.861e-59 | 6.88e-55

Figure S10. Get High-res Image As an example, this figure shows the association of FGF18 to 'TUMOR.STAGE'. P value = 6.89e-72 with Spearman correlation analysis.

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

5965 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

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

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 198
| YES | 1446
| Significant markers | N = 5965
| Higher in YES | 2978
| Higher in NO | 2987

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 | 22.07 | 1.262e-78 | 2.25e-74 | 0.7768
TCF21 | 22.24 | 9.051e-75 | 1.61e-70 | 0.794
CYP3A4 | 20.83 | 9.786e-74 | 1.74e-69 | 0.7658
AADAC | 21.44 | 7.099e-73 | 1.26e-68 | 0.7785
CYP3A7 | 20.7 | 4.022e-72 | 7.16e-68 | 0.7568
REG1A | 20.57 | 4.397e-69 | 7.83e-65 | 0.7794
CCDC71 | 22.24 | 2.821e-68 | 5.02e-64 | 0.8278
MAP2K7 | 21.04 | 8.975e-67 | 1.6e-62 | 0.7924
PDZD3 | 18.08 | 1.499e-64 | 2.67e-60 | 0.6854
FBXO34 | 20.17 | 2.054e-63 | 3.66e-59 | 0.7811

Figure S11. Get High-res Image As an example, this figure shows the association of CYP3A5 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.26e-78 with T-test analysis.

Clinical variable #12: 'NEOADJUVANT.THERAPY'

7746 genes related to 'NEOADJUVANT.THERAPY'.

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

NEOADJUVANT.THERAPY | Labels | N
| NO | 714
| YES | 930
| Significant markers | N = 7746
| Higher in YES | 3927
| Higher in NO | 3819

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
--- | --- | --- | --- | ---
UGT1A6 | 21.73 | 2.26e-90 | 4.03e-86 | 0.7338
ATP6V1B1 | -21.51 | 7.552e-90 | 1.35e-85 | 0.7743
NPAS3 | -21.56 | 9.588e-90 | 1.71e-85 | 0.7822
SCARA3 | -21.4 | 1.597e-88 | 2.84e-84 | 0.7765
GPX2 | 21.31 | 8.718e-87 | 1.55e-82 | 0.7267
PPARG | 20.76 | 3.469e-85 | 6.18e-81 | 0.7578
ZNF667 | -20.75 | 5.219e-85 | 9.29e-81 | 0.7638
RNF150 | -20.76 | 1.436e-84 | 2.56e-80 | 0.7652
SLC27A6 | -20.7 | 7.841e-84 | 1.4e-79 | 0.7733
EPS8 | 20.2 | 4.018e-81 | 7.15e-77 | 0.7548

Figure S12. Get High-res Image As an example, this figure shows the association of UGT1A6 to 'NEOADJUVANT.THERAPY'. P value = 2.26e-90 with T-test analysis.

Methods & Data
Input

- Expresson data file = PANCANCER.medianexp.txt

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

- Number of patients = 1644

- 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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