Correlation between mRNA expression and clinical features
PANCANCER cohort with 12 disease types (Primary solid tumor)
23 May 2013 | analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1Q52MPG
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1Q52MPG
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 15 clinical features across 1593 samples, statistically thresholded by Q value < 0.05, 12 clinical features related to at least one genes.

- 3048 genes correlated to 'Time to Death'.

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

- 3682 genes correlated to 'AGE'.

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

- 17229 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

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

- 8979 genes correlated to 'GENDER'.

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

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

- PPP1R9A , VASN , METTL8 , MARCH7 , ZNF503 , ...

- 17150 genes correlated to 'HISTOLOGICAL.TYPE'.

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

- 5806 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- CYP3A5 , CYP3A4 , CYP3A7 , MAP2K7 , TCF21 , ...

- 2 genes correlated to 'YEAROFTOBACCOSMOKINGONSET'.

- MMP10 , ALS2CR4

- 576 genes correlated to 'DISTANT.METASTASIS'.

- VIL1 , MUC13 , FABP1 , SPACA3 , ACF , ...

- 9839 genes correlated to 'LYMPH.NODE.METASTASIS'.

- FXYD2 , EFHD1 , GATA3 , OVOL2 , TRPS1 , ...

- 2084 genes correlated to 'COMPLETENESS.OF.RESECTION'.

- NPR1 , WIT1 , THRSP , KLHL14 , S100A1 , ...

- 10650 genes correlated to 'NEOPLASM.DISEASESTAGE'.

- SCGB3A2 , MUPCDH , HNF1A , PDZD3 , CLRN3 , ...

- No genes correlated to 'TUMOR.STAGE', 'NUMBERPACKYEARSSMOKED', and 'NUMBER.OF.LYMPH.NODES'.

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=3048 | shorter survival | N=1442 | longer survival | N=1606
AGE | Spearman correlation test | N=3682 | older | N=1744 | younger | N=1938
PRIMARY SITE OF DISEASE | ANOVA test | N=17229 |  |  |  |
GENDER | t test | N=8979 | male | N=4341 | female | N=4638
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=196 | higher score | N=92 | lower score | N=104
HISTOLOGICAL TYPE | ANOVA test | N=17150 |  |  |  |
TUMOR STAGE | Spearman correlation test | N=0 |  |  |  |
RADIATIONS RADIATION REGIMENINDICATION | t test | N=5806 | yes | N=2804 | no | N=3002
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=0 |  |  |  |
YEAROFTOBACCOSMOKINGONSET | Spearman correlation test | N=2 | higher yearoftobaccosmokingonset | N=0 | lower yearoftobaccosmokingonset | N=2
DISTANT METASTASIS | ANOVA test | N=576 |  |  |  |
LYMPH NODE METASTASIS | ANOVA test | N=9839 |  |  |  |
COMPLETENESS OF RESECTION | ANOVA test | N=2084 |  |  |  |
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |  |  |  |
NEOPLASM DISEASESTAGE | ANOVA test | N=10650 |  |  |  |

Clinical variable #1: 'Time to Death'

3048 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=22.7)
| censored | N = 1006
| death | N = 438
| Significant markers | N = 3048
| associated with shorter survival | 1442
| associated with longer survival | 1606

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 | 0.605
ASS1 | 1.33 | 0 | 0 | 0.623
IGSF11 | 1.36 | 0 | 0 | 0.644
UPK1B | 1.21 | 0 | 0 | 0.637
C4ORF32 | 0.78 | 0 | 0 | 0.38
ZRSR1 | 0.55 | 0 | 0 | 0.349
MDS1 | 1.38 | 0 | 0 | 0.625
GALNT12 | 1.32 | 0 | 0 | 0.616
NUBP1 | 0.47 | 0 | 0 | 0.356
DAPL1 | 1.14 | 0 | 0 | 0.624

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'

3682 genes related to 'AGE'.

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

AGE | Mean (SD) | 61.39 (13)
| Significant markers | N = 3682
| pos. correlated | 1744
| neg. correlated | 1938

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 | -0.2892 | 9.188e-32 | 1.64e-27
COL18A1 | -0.2758 | 6.342e-29 | 1.13e-24
DUOX2 | 0.2752 | 8.485e-29 | 1.51e-24
LDOC1 | -0.2683 | 2.09e-27 | 3.72e-23
GALNTL1 | -0.267 | 3.747e-27 | 6.67e-23
OBSL1 | -0.2642 | 1.335e-26 | 2.38e-22
FOXF1 | 0.2611 | 5.404e-26 | 9.62e-22
CYP2C18 | 0.2585 | 1.69e-25 | 3.01e-21
NOTCH2 | -0.2559 | 5.25e-25 | 9.35e-21
BBOX1 | -0.2557 | 5.714e-25 | 1.02e-20

Figure S2. Get High-res Image As an example, this figure shows the association of GREB1 to 'AGE'. P value = 9.19e-32 with Spearman correlation analysis. The straight line presents the best linear regression.

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

17229 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 | 526
| COLON | 152
| ENDOMETRIAL | 54
| KIDNEY | 72
| LUNG | 186
| OMENTUM | 2
| OVARY | 529
| PERITONEUM OVARY | 2
| RECTUM | 68
| Significant markers | N = 17229

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'

8979 genes related to 'GENDER'.

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

GENDER | Labels | N
| FEMALE | 1304
| MALE | 289
| Significant markers | N = 8979
| Higher in MALE | 4341
| Higher in FEMALE | 4638

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 | -35.87 | 9.367e-164 | 1.67e-159 | 0.8775
DDX3Y | 53.23 | 5.05e-163 | 9e-159 | 0.9837
RSPO1 | -31.07 | 4.803e-162 | 8.56e-158 | 0.8428
RPS4Y1 | 51.71 | 2.642e-155 | 4.71e-151 | 0.9711
EIF1AY | 49.21 | 1.083e-151 | 1.93e-147 | 0.9842
RPS4Y2 | 48.53 | 1.689e-147 | 3.01e-143 | 0.9814
ERBB4 | -32.57 | 2.549e-147 | 4.54e-143 | 0.8586
JARID1D | 44.6 | 2.007e-146 | 3.57e-142 | 0.9767
SCGB2A2 | -29.39 | 1.805e-145 | 3.21e-141 | 0.8531
CYORF15A | 43.7 | 2.34e-139 | 4.17e-135 | 0.981

Figure S4. Get High-res Image As an example, this figure shows the association of ESR1 to 'GENDER'. P value = 9.37e-164 with T-test analysis.

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

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

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

KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 60.22 (34)
| Significant markers | N = 196
| pos. correlated | 92
| neg. correlated | 104

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 | 0.591 | 4.461e-10 | 7.95e-06
VASN | 0.5685 | 2.77e-09 | 4.93e-05
METTL8 | -0.5495 | 1.168e-08 | 0.000208
MARCH7 | -0.5488 | 1.234e-08 | 0.00022
ZNF503 | 0.5415 | 2.087e-08 | 0.000372
ADK | -0.5406 | 2.225e-08 | 0.000396
PCYT1A | -0.5405 | 2.235e-08 | 0.000398
INSIG2 | -0.5394 | 2.423e-08 | 0.000432
ARHGEF17 | 0.5392 | 2.453e-08 | 0.000437
POGZ | 0.5364 | 2.984e-08 | 0.000531

Figure S5. Get High-res Image As an example, this figure shows the association of PPP1R9A to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 4.46e-10 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #6: 'HISTOLOGICAL.TYPE'

17150 genes related to 'HISTOLOGICAL.TYPE'.

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

HISTOLOGICAL.TYPE | Labels | N
| COLON ADENOCARCINOMA | 127
| COLON MUCINOUS ADENOCARCINOMA | 24
| ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 41
| INFILTRATING DUCTAL CARCINOMA | 449
| INFILTRATING LOBULAR CARCINOMA | 41
| KIDNEY CLEAR CELL RENAL CARCINOMA | 72
| 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
| MEDULLARY CARCINOMA | 1
| MIXED HISTOLOGY (PLEASE SPECIFY) | 11
| MIXED SEROUS AND ENDOMETRIOID | 1
| MUCINOUS CARCINOMA | 2
| OTHER SPECIFY | 22
| RECTAL ADENOCARCINOMA | 58
| RECTAL MUCINOUS ADENOCARCINOMA | 7
| SEROUS CYSTADENOCARCINOMA | 533
| SEROUS ENDOMETRIAL ADENOCARCINOMA | 12
| Significant markers | N = 17150

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
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 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: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S13. Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE | Mean (SD) | 3.17 (0.48)
|  | N
| Stage 1 | 2
| Stage 2 | 2
| Stage 3 | 133
| Stage 4 | 35
| Significant markers | N = 0

Clinical variable #8: 'RADIATIONS.RADIATION.REGIMENINDICATION'

5806 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S14. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 180
| YES | 1413
| Significant markers | N = 5806
| Higher in YES | 2804
| Higher in NO | 3002

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

Table S15. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
CYP3A5 | 22.2 | 5.34e-77 | 9.51e-73 | 0.7876
CYP3A4 | 20.43 | 4.757e-69 | 8.47e-65 | 0.7735
CYP3A7 | 20.48 | 6.735e-69 | 1.2e-64 | 0.765
MAP2K7 | 21.46 | 1.143e-65 | 2.04e-61 | 0.8093
TCF21 | 20.88 | 5.069e-65 | 9.03e-61 | 0.7933
AADAC | 19.82 | 6.153e-62 | 1.1e-57 | 0.7706
CCDC71 | 21.07 | 9.49e-62 | 1.69e-57 | 0.8196
PDZD3 | 17.37 | 3.482e-59 | 6.2e-55 | 0.6903
REG1A | 19.03 | 1.149e-58 | 2.05e-54 | 0.7743
CHMP4B | 19.79 | 2.297e-56 | 4.09e-52 | 0.809

Figure S7. Get High-res Image As an example, this figure shows the association of CYP3A5 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 5.34e-77 with T-test analysis.

Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S16. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED | Mean (SD) | 53.05 (35)
| Significant markers | N = 0

Clinical variable #10: 'YEAROFTOBACCOSMOKINGONSET'

2 genes related to 'YEAROFTOBACCOSMOKINGONSET'.

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

YEAROFTOBACCOSMOKINGONSET | Mean (SD) | 1959.74 (11)
| Significant markers | N = 2
| pos. correlated | 0
| neg. correlated | 2

List of 2 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S18. Get Full Table List of 2 genes significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
MMP10 | -0.4479 | 4.625e-07 | 0.00824
ALS2CR4 | -0.4273 | 1.724e-06 | 0.0307

Figure S8. Get High-res Image As an example, this figure shows the association of MMP10 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 4.63e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #11: 'DISTANT.METASTASIS'

576 genes related to 'DISTANT.METASTASIS'.

Table S19. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS | Labels | N
| CM0 (I+) | 2
| M0 | 925
| M1 | 58
| M1A | 1
| MX | 14
| Significant markers | N = 576

List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

Table S20. Get Full Table List of top 10 genes differentially expressed by 'DISTANT.METASTASIS'

| ANOVA_P | Q
--- | --- | ---
VIL1 | 8.478e-13 | 1.51e-08
MUC13 | 2.841e-12 | 5.06e-08
FABP1 | 4.306e-12 | 7.67e-08
SPACA3 | 4.683e-12 | 8.34e-08
ACF | 7.447e-12 | 1.33e-07
CALML4 | 7.796e-12 | 1.39e-07
TMEM25 | 8.062e-12 | 1.44e-07
IL22RA1 | 8.786e-12 | 1.56e-07
PCLKC | 1.225e-11 | 2.18e-07
PDZD3 | 1.317e-11 | 2.35e-07

Figure S9. Get High-res Image As an example, this figure shows the association of VIL1 to 'DISTANT.METASTASIS'. P value = 8.48e-13 with ANOVA analysis.

Clinical variable #12: 'LYMPH.NODE.METASTASIS'

9839 genes related to 'LYMPH.NODE.METASTASIS'.

Table S21. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS | Labels | N
| N0 | 428
| N0 (I+) | 16
| N0 (I-) | 101
| N1 | 146
| N1A | 78
| N1B | 21
| N1C | 2
| N1MI | 13
| N2 | 91
| N2A | 30
| N3 | 15
| N3A | 18
| N3C | 1
| NX | 46
| Significant markers | N = 9839

List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S22. Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

| ANOVA_P | Q
--- | --- | ---
FXYD2 | 2.922e-72 | 5.21e-68
EFHD1 | 2.266e-70 | 4.04e-66
GATA3 | 7.001e-68 | 1.25e-63
OVOL2 | 1.062e-66 | 1.89e-62
TRPS1 | 1.272e-66 | 2.27e-62
GALNTL1 | 3.045e-62 | 5.42e-58
CDH16 | 7.022e-62 | 1.25e-57
SCGB2A2 | 1.407e-61 | 2.51e-57
C14ORF105 | 1.311e-60 | 2.33e-56
N4BP3 | 3.338e-60 | 5.94e-56

Figure S10. Get High-res Image As an example, this figure shows the association of FXYD2 to 'LYMPH.NODE.METASTASIS'. P value = 2.92e-72 with ANOVA analysis.

Clinical variable #13: 'COMPLETENESS.OF.RESECTION'

2084 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S23. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION | Labels | N
| R0 | 403
| R1 | 38
| R2 | 36
| RX | 7
| Significant markers | N = 2084

List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S24. Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

| ANOVA_P | Q
--- | --- | ---
NPR1 | 2.763e-36 | 4.92e-32
WIT1 | 5.858e-35 | 1.04e-30
THRSP | 2.077e-34 | 3.7e-30
KLHL14 | 1.748e-32 | 3.11e-28
S100A1 | 8.042e-32 | 1.43e-27
WT1 | 1.283e-31 | 2.28e-27
DOK5 | 7.471e-31 | 1.33e-26
LYPD1 | 7.893e-28 | 1.41e-23
SCGB1D2 | 6.032e-27 | 1.07e-22
SCGB1C1 | 1.615e-26 | 2.88e-22

Figure S11. Get High-res Image As an example, this figure shows the association of NPR1 to 'COMPLETENESS.OF.RESECTION'. P value = 2.76e-36 with ANOVA analysis.

Clinical variable #14: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S25. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES | Mean (SD) | 1.94 (4)
| Significant markers | N = 0

Clinical variable #15: 'NEOPLASM.DISEASESTAGE'

10650 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S26. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE | Labels | N
| STAGE I | 129
| STAGE IA | 73
| STAGE IB | 78
| STAGE II | 28
| STAGE IIA | 258
| STAGE IIB | 145
| STAGE III | 24
| STAGE IIIA | 102
| STAGE IIIB | 52
| STAGE IIIC | 39
| STAGE IV | 57
| STAGE IVA | 1
| STAGE TIS | 1
| STAGE X | 16
| Significant markers | N = 10650

List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S27. Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

| ANOVA_P | Q
--- | --- | ---
SCGB3A2 | 1.701e-87 | 3.03e-83
MUPCDH | 5.802e-85 | 1.03e-80
HNF1A | 7.145e-84 | 1.27e-79
PDZD3 | 9.868e-84 | 1.76e-79
CLRN3 | 1.743e-83 | 3.1e-79
LRRC19 | 5.968e-82 | 1.06e-77
USH1C | 6.653e-82 | 1.18e-77
NR1H4 | 1.731e-81 | 3.08e-77
GAL3ST1 | 2.38e-81 | 4.24e-77
SCGB1A1 | 2.215e-80 | 3.94e-76

Figure S12. Get High-res Image As an example, this figure shows the association of SCGB3A2 to 'NEOPLASM.DISEASESTAGE'. P value = 1.7e-87 with ANOVA analysis.

Methods & Data
Input

- Expresson data file = PANCAN12-TP.medianexp.txt

- Clinical data file = PANCAN12-TP.clin.merged.picked.txt

- Number of patients = 1593

- Number of genes = 17814

- 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

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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