Correlation between mRNAseq expression and clinical features
Glioma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C12Z14JJ
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C12Z14JJ
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features.

Summary

Testing the association between 18325 genes and 9 clinical features across 627 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 7 clinical features related to at least one genes.

  • 30 genes correlated to 'YEARS_TO_BIRTH'.

    • ABI1|10006 ,  RBM17|84991 ,  CTBP2|1488 ,  ZMYND11|10771 ,  GLUD1|2746 ,  ...

  • 30 genes correlated to 'PRIMARY_SITE_OF_DISEASE'.

    • EEF1A1P9|441032 ,  LOC442454|442454 ,  NACAP1|83955 ,  HNRNPA3P1|10151 ,  SUMO1P3|474338 ,  ...

  • 4 genes correlated to 'GENDER'.

    • NCRNA00183|554203 ,  CYORF15A|246126 ,  HDHD1A|8226 ,  CYORF15B|84663

  • 30 genes correlated to 'KARNOFSKY_PERFORMANCE_SCORE'.

    • ZBTB47|92999 ,  EEF1A1P9|441032 ,  VAV3|10451 ,  SEPHS2|22928 ,  LOC541471|541471 ,  ...

  • 30 genes correlated to 'HISTOLOGICAL_TYPE'.

    • GPX7|2882 ,  AK2|204 ,  CAPZA1|829 ,  DDOST|1650 ,  MED8|112950 ,  ...

  • 30 genes correlated to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

    • ADAMTS13|11093 ,  NPIP|9284 ,  AGAP4|119016 ,  GRIPAP1|56850 ,  SH2B1|25970 ,  ...

  • 30 genes correlated to 'RACE'.

    • C21ORF56|84221 ,  SEC1|653677 ,  LRRC37A2|474170 ,  LRRC37A|9884 ,  DHRS4L2|317749 ,  ...

  • No genes correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', and 'ETHNICITY'.

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 P value < 0.05 and Q value < 0.3.

Clinical feature Statistical test Significant genes Associated with                 Associated with
DAYS_TO_DEATH_OR_LAST_FUP Cox regression test   N=0        
YEARS_TO_BIRTH Spearman correlation test N=30 older N=16 younger N=14
PRIMARY_SITE_OF_DISEASE Wilcoxon test N=30 central nervous system N=30 brain N=0
GENDER Wilcoxon test N=4 male N=4 female N=0
KARNOFSKY_PERFORMANCE_SCORE Spearman correlation test N=30 higher score N=20 lower score N=10
HISTOLOGICAL_TYPE Kruskal-Wallis test N=30        
RADIATIONS_RADIATION_REGIMENINDICATION Wilcoxon test N=30 yes N=30 no N=0
RACE Kruskal-Wallis test N=30        
ETHNICITY Wilcoxon test   N=0        
Clinical variable #1: 'DAYS_TO_DEATH_OR_LAST_FUP'

No gene related to 'DAYS_TO_DEATH_OR_LAST_FUP'.

Table S1.  Basic characteristics of clinical feature: 'DAYS_TO_DEATH_OR_LAST_FUP'

DAYS_TO_DEATH_OR_LAST_FUP Duration (Months) 0-211.2 (median=16.2)
  censored N = 415
  death N = 211
     
  Significant markers N = 0
Clinical variable #2: 'YEARS_TO_BIRTH'

30 genes related to 'YEARS_TO_BIRTH'.

Table S2.  Basic characteristics of clinical feature: 'YEARS_TO_BIRTH'

YEARS_TO_BIRTH Mean (SD) 47.06 (15)
  Significant markers N = 30
  pos. correlated 16
  neg. correlated 14
List of top 10 genes differentially expressed by 'YEARS_TO_BIRTH'

Table S3.  Get Full Table List of top 10 genes significantly correlated to 'YEARS_TO_BIRTH' by Spearman correlation test

SpearmanCorr corrP Q
ABI1|10006 -0.5498 9.788e-51 1.79e-46
RBM17|84991 -0.5383 2.585e-48 2.37e-44
CTBP2|1488 -0.5319 5.245e-47 3.2e-43
ZMYND11|10771 -0.5306 9.329e-47 4.27e-43
GLUD1|2746 -0.5283 2.745e-46 1.01e-42
PCDH15|65217 -0.5282 3.987e-46 1.22e-42
SLC27A3|11000 0.5184 2.397e-44 6.27e-41
CNTN3|5067 -0.52 3.55e-44 8.13e-41
CHI3L1|1116 0.5168 4.857e-44 9.89e-41
FAM171A1|221061 -0.5113 5.325e-43 9.07e-40
Clinical variable #3: 'PRIMARY_SITE_OF_DISEASE'

30 genes related to 'PRIMARY_SITE_OF_DISEASE'.

Table S4.  Basic characteristics of clinical feature: 'PRIMARY_SITE_OF_DISEASE'

PRIMARY_SITE_OF_DISEASE Labels N
  BRAIN 152
  CENTRAL NERVOUS SYSTEM 475
     
  Significant markers N = 30
  Higher in CENTRAL NERVOUS SYSTEM 30
  Higher in BRAIN 0
List of top 10 genes differentially expressed by 'PRIMARY_SITE_OF_DISEASE'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'PRIMARY_SITE_OF_DISEASE'

W(pos if higher in 'CENTRAL NERVOUS SYSTEM') wilcoxontestP Q AUC
EEF1A1P9|441032 72200 5.481e-77 2.66e-73 1
LOC442454|442454 72200 5.481e-77 2.66e-73 1
NACAP1|83955 72200 5.481e-77 2.66e-73 1
HNRNPA3P1|10151 72194 5.805e-77 2.66e-73 0.9999
SUMO1P3|474338 84 1.225e-76 3.97e-73 0.9988
FTHL3|2498 71725 1.3e-76 3.97e-73 1
ATP5EP2|432369 309 1.045e-75 2.74e-72 0.9957
GCSH|2653 70621 3.24e-75 7.42e-72 0.9978
PA2G4P4|647033 460 4.374e-75 8.63e-72 0.9936
RPL23P8|222901 71349 4.71e-75 8.63e-72 0.9948
Clinical variable #4: 'GENDER'

4 genes related to 'GENDER'.

Table S6.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 261
  MALE 366
     
  Significant markers N = 4
  Higher in MALE 4
  Higher in FEMALE 0
List of 4 genes differentially expressed by 'GENDER'

Table S7.  Get Full Table List of 4 genes differentially expressed by 'GENDER'. 26 significant gene(s) located in sex chromosomes is(are) filtered out.

W(pos if higher in 'MALE') wilcoxontestP Q AUC
NCRNA00183|554203 13132 4.15e-54 7.6e-51 0.8625
CYORF15A|246126 29635 5.123e-45 6.71e-42 0.9996
HDHD1A|8226 19922 1.37e-35 1.39e-32 0.7914
CYORF15B|84663 20113 7.164e-33 6.56e-30 0.9992
Clinical variable #5: 'KARNOFSKY_PERFORMANCE_SCORE'

30 genes related to 'KARNOFSKY_PERFORMANCE_SCORE'.

Table S8.  Basic characteristics of clinical feature: 'KARNOFSKY_PERFORMANCE_SCORE'

KARNOFSKY_PERFORMANCE_SCORE Mean (SD) 84.18 (14)
  Significant markers N = 30
  pos. correlated 20
  neg. correlated 10
List of top 10 genes differentially expressed by 'KARNOFSKY_PERFORMANCE_SCORE'

Table S9.  Get Full Table List of top 10 genes significantly correlated to 'KARNOFSKY_PERFORMANCE_SCORE' by Spearman correlation test

SpearmanCorr corrP Q
ZBTB47|92999 0.4794 2.113e-23 3.87e-19
EEF1A1P9|441032 0.4684 2.805e-22 2.57e-18
VAV3|10451 -0.464 7.599e-22 4.64e-18
SEPHS2|22928 -0.4576 3.19e-21 1.29e-17
LOC541471|541471 -0.4572 3.506e-21 1.29e-17
SEC24D|9871 -0.4559 4.659e-21 1.42e-17
NCRNA00152|112597 -0.4535 7.95e-21 2.08e-17
LOC728643|728643 0.4543 1.694e-20 3.88e-17
RPL17|6139 0.4482 2.531e-20 5e-17
DGCR2|9993 0.4473 3.059e-20 5e-17
Clinical variable #6: 'HISTOLOGICAL_TYPE'

30 genes related to 'HISTOLOGICAL_TYPE'.

Table S10.  Basic characteristics of clinical feature: 'HISTOLOGICAL_TYPE'

HISTOLOGICAL_TYPE Labels N
  ASTROCYTOMA 176
  GLIOBLASTOMA MULTIFORME (GBM) 1
  OLIGOASTROCYTOMA 119
  OLIGODENDROGLIOMA 180
  TREATED PRIMARY GBM 1
  UNTREATED PRIMARY (DE NOVO) GBM 150
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL_TYPE'

kruskal_wallis_P Q
GPX7|2882 2.477e-81 4.54e-77
AK2|204 1.513e-79 1.39e-75
CAPZA1|829 1.142e-77 6.98e-74
DDOST|1650 2.959e-77 1.36e-73
MED8|112950 6.129e-75 2.25e-71
WDR77|79084 1.35e-74 4.12e-71
HNRNPA3P1|10151 4.718e-74 1.24e-70
UBE2MP1|606551 8.266e-74 1.89e-70
SUMO1P3|474338 1.427e-73 2.9e-70
NACAP1|83955 3.421e-73 6.27e-70
Clinical variable #7: 'RADIATIONS_RADIATION_REGIMENINDICATION'

30 genes related to 'RADIATIONS_RADIATION_REGIMENINDICATION'.

Table S12.  Basic characteristics of clinical feature: 'RADIATIONS_RADIATION_REGIMENINDICATION'

RADIATIONS_RADIATION_REGIMENINDICATION Labels N
  NO 194
  YES 433
     
  Significant markers N = 30
  Higher in YES 30
  Higher in NO 0
List of top 10 genes differentially expressed by 'RADIATIONS_RADIATION_REGIMENINDICATION'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS_RADIATION_REGIMENINDICATION'

W(pos if higher in 'YES') wilcoxontestP Q AUC
ADAMTS13|11093 67156 3.673e-33 6.73e-29 0.7995
NPIP|9284 66312 4.383e-31 4.02e-27 0.7894
AGAP4|119016 66102 1.405e-30 8.58e-27 0.7869
GRIPAP1|56850 66045.5 1.919e-30 8.79e-27 0.7862
SH2B1|25970 65911 4.018e-30 1.47e-26 0.7846
NEURL4|84461 65840 5.926e-30 1.81e-26 0.7838
SEC31B|25956 65637 1.788e-29 4.68e-26 0.7814
EXD3|54932 65241 1.502e-28 3.44e-25 0.7767
TUBGCP6|85378 64965 6.48e-28 1.32e-24 0.7734
TMED2|10959 19079 8.083e-28 1.42e-24 0.7729
Clinical variable #8: 'RACE'

30 genes related to 'RACE'.

Table S14.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  AMERICAN INDIAN OR ALASKA NATIVE 1
  ASIAN 13
  BLACK OR AFRICAN AMERICAN 25
  WHITE 576
     
  Significant markers N = 30
List of top 10 genes differentially expressed by 'RACE'

Table S15.  Get Full Table List of top 10 genes differentially expressed by 'RACE'

kruskal_wallis_P Q
C21ORF56|84221 1.08e-07 0.00198
SEC1|653677 3.277e-07 0.003
LRRC37A2|474170 7.335e-07 0.00448
LRRC37A|9884 4.195e-06 0.0192
DHRS4L2|317749 5.862e-06 0.0215
GSTM1|2944 7.722e-06 0.0236
PPIL3|53938 9.972e-06 0.0261
PYROXD2|84795 3.689e-05 0.0845
HRNR|388697 6.583e-05 0.122
ARMC10|83787 6.675e-05 0.122
Clinical variable #9: 'ETHNICITY'

No gene related to 'ETHNICITY'.

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

ETHNICITY Labels N
  HISPANIC OR LATINO 21
  NOT HISPANIC OR LATINO 547
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = GBMLGG-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

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

  • Number of patients = 627

  • Number of genes = 18325

  • Number of clinical features = 9

Selected clinical features

  • For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .

  • Survival time data

    • Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.

      • if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'

      • if 'vital_status'==0(alive),

        • if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'

        • if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.

      • if 'vital_status'==NA,excludes this case in survival analysis and report the case.

    • cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .

  • This analysis excluded clinical variables that has only NA values.

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

Wilcoxon rank sum test (Mann-Whitney U test)

For two groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.

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] Mann and Whitney, On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other, Annals of Mathematical Statistics 18 (1), 50-60 (1947)
[4] 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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