Correlation between mRNAseq expression and clinical features
Brain Lower Grade Glioma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1W37TKC
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1W37TKC
Overview
Introduction

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

Summary

Testing the association between 18324 genes and 6 clinical features across 231 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

  • 664 genes correlated to 'Time to Death'.

    • SLITRK5|26050 ,  FNDC3B|64778 ,  RANBP17|64901 ,  CBARA1|10367 ,  CRTAC1|55118 ,  ...

  • 191 genes correlated to 'AGE'.

    • PRSS35|167681 ,  SFRP2|6423 ,  TRMT2B|79979 ,  SYT6|148281 ,  GRPEL2|134266 ,  ...

  • 29 genes correlated to 'GENDER'.

    • XIST|7503 ,  ZFY|7544 ,  RPS4Y1|6192 ,  PRKY|5616 ,  KDM5D|8284 ,  ...

  • 2965 genes correlated to 'HISTOLOGICAL.TYPE'.

    • TXNDC12|51060 ,  AK2|204 ,  WLS|79971 ,  RHOC|389 ,  SEP15|9403 ,  ...

  • 1 gene correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • C17ORF63|55731

  • No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'

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=664 shorter survival N=306 longer survival N=358
AGE Spearman correlation test N=191 older N=84 younger N=107
GENDER t test N=29 male N=17 female N=12
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE ANOVA test N=2965        
RADIATIONS RADIATION REGIMENINDICATION t test N=1 yes N=0 no N=1
Clinical variable #1: 'Time to Death'

664 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-211.2 (median=14.5)
  censored N = 176
  death N = 55
     
  Significant markers N = 664
  associated with shorter survival 306
  associated with longer survival 358
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
SLITRK5|26050 0.41 1.088e-13 2e-09 0.255
FNDC3B|64778 4 1.197e-12 2.2e-08 0.784
RANBP17|64901 0.63 2.374e-12 4.3e-08 0.311
CBARA1|10367 0.14 3.787e-12 6.9e-08 0.232
CRTAC1|55118 0.64 4.56e-12 8.4e-08 0.24
CUEDC2|79004 0.09 4.816e-12 8.8e-08 0.237
NTNG2|84628 0.48 7.25e-12 1.3e-07 0.207
LOC254559|254559 0.53 7.705e-12 1.4e-07 0.227
PVRL1|5818 0.35 1.19e-11 2.2e-07 0.271
ZDHHC22|283576 0.55 1.24e-11 2.3e-07 0.27

Figure S1.  Get High-res Image As an example, this figure shows the association of SLITRK5|26050 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 1.09e-13 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

191 genes related to 'AGE'.

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

AGE Mean (SD) 42.73 (13)
  Significant markers N = 191
  pos. correlated 84
  neg. correlated 107
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
PRSS35|167681 -0.4377 3.137e-12 5.75e-08
SFRP2|6423 -0.4325 5.989e-12 1.1e-07
TRMT2B|79979 0.4255 1.417e-11 2.6e-07
SYT6|148281 -0.4199 2.787e-11 5.11e-07
GRPEL2|134266 0.4027 2.029e-10 3.72e-06
SIM2|6493 0.4025 2.088e-10 3.82e-06
ZDHHC19|131540 -0.3978 5.456e-10 9.99e-06
DTX4|23220 -0.3913 7.192e-10 1.32e-05
TMIGD2|126259 -0.391 7.371e-10 1.35e-05
EEPD1|80820 -0.3903 8e-10 1.47e-05

Figure S2.  Get High-res Image As an example, this figure shows the association of PRSS35|167681 to 'AGE'. P value = 3.14e-12 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

29 genes related to 'GENDER'.

Table S5.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 103
  MALE 128
     
  Significant markers N = 29
  Higher in MALE 17
  Higher in FEMALE 12
List of top 10 genes differentially expressed by 'GENDER'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
XIST|7503 -57.68 2.379e-135 4.36e-131 0.9999
ZFY|7544 67.18 4.971e-101 9.11e-97 1
RPS4Y1|6192 60.8 2.628e-87 4.81e-83 1
PRKY|5616 36.7 1.523e-84 2.79e-80 0.9998
KDM5D|8284 72 2.332e-79 4.27e-75 1
NLGN4Y|22829 37.1 7.743e-78 1.42e-73 0.9972
USP9Y|8287 75.86 4.291e-76 7.86e-72 1
DDX3Y|8653 71.25 2.572e-75 4.71e-71 1
TSIX|9383 -26.82 8.498e-63 1.56e-58 1
EIF1AY|9086 78.19 3.037e-59 5.56e-55 1

Figure S3.  Get High-res Image As an example, this figure shows the association of XIST|7503 to 'GENDER'. P value = 2.38e-135 with T-test analysis.

Clinical variable #4: 'KARNOFSKY.PERFORMANCE.SCORE'

No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S7.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 88.12 (11)
  Significant markers N = 0
Clinical variable #5: 'HISTOLOGICAL.TYPE'

2965 genes related to 'HISTOLOGICAL.TYPE'.

Table S8.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  ASTROCYTOMA 71
  OLIGOASTROCYTOMA 65
  OLIGODENDROGLIOMA 94
     
  Significant markers N = 2965
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S9.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
TXNDC12|51060 6.623e-23 1.21e-18
AK2|204 1.563e-22 2.86e-18
WLS|79971 5.702e-22 1.04e-17
RHOC|389 5.764e-22 1.06e-17
SEP15|9403 9.128e-22 1.67e-17
TRAPPC3|27095 2.947e-21 5.4e-17
STK40|83931 4.755e-21 8.71e-17
GNG5|2787 4.876e-21 8.93e-17
CAP1|10487 5.428e-21 9.94e-17
LRRC42|115353 1.584e-20 2.9e-16

Figure S4.  Get High-res Image As an example, this figure shows the association of TXNDC12|51060 to 'HISTOLOGICAL.TYPE'. P value = 6.62e-23 with ANOVA analysis.

Clinical variable #6: 'RADIATIONS.RADIATION.REGIMENINDICATION'

One gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S10.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 90
  YES 141
     
  Significant markers N = 1
  Higher in YES 0
  Higher in NO 1
List of one gene differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S11.  Get Full Table List of one gene differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
C17ORF63|55731 -4.97 1.793e-06 0.0329 0.6838

Figure S5.  Get High-res Image As an example, this figure shows the association of C17ORF63|55731 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.79e-06 with T-test analysis.

Methods & Data
Input

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

  • Clinical data file = LGG-TP.clin.merged.picked.txt

  • Number of patients = 231

  • Number of genes = 18324

  • Number of clinical features = 6

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

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

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

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] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[4] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[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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