Correlation between mRNAseq expression and clinical features
Esophageal Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1794394
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1794394
Overview
Introduction

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

Summary

Testing the association between 23891 genes and 8 clinical features across 51 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

  • 21 genes correlated to 'AGE'.

    • CEP97|79598_CALCULATED ,  DDB2|1643_CALCULATED ,  KPNA7|402569_CALCULATED ,  ODZ4|26011|1OF2_CALCULATED ,  FOXE1|2304_CALCULATED ,  ...

  • 3 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • CS330190|?|1OF2_CALCULATED ,  DQ600234|?_CALCULATED ,  DQ573774|?_CALCULATED

  • 13 genes correlated to 'PATHOLOGY.T.STAGE'.

    • AX747838|?_CALCULATED ,  LOC731275|731275_CALCULATED ,  KDM6A|7403_CALCULATED ,  MIR_584|?|5OF49_CALCULATED ,  UNQ2790|?_CALCULATED ,  ...

  • 1 gene correlated to 'PATHOLOGY.M.STAGE'.

    • TMEM132D|121256_CALCULATED

  • 16 genes correlated to 'GENDER'.

    • PRKY|5616_CALCULATED ,  EIF1AY|9086_CALCULATED ,  ANKRD5|63926_CALCULATED ,  USP9Y|8287_CALCULATED ,  AK126491|?_CALCULATED ,  ...

  • No genes correlated to 'Time to Death', 'PATHOLOGY.N.STAGE', and 'NUMBERPACKYEARSSMOKED'.

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=0        
AGE Spearman correlation test N=21 older N=7 younger N=14
NEOPLASM DISEASESTAGE ANOVA test N=3        
PATHOLOGY T STAGE Spearman correlation test N=13 higher stage N=0 lower stage N=13
PATHOLOGY N STAGE Spearman correlation test   N=0        
PATHOLOGY M STAGE ANOVA test N=1        
GENDER t test N=16 male N=7 female N=9
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

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

Time to Death Duration (Months) 0-30.7 (median=0.8)
  censored N = 36
  death N = 13
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

21 genes related to 'AGE'.

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

AGE Mean (SD) 62.71 (12)
  Significant markers N = 21
  pos. correlated 7
  neg. correlated 14
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

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

SpearmanCorr corrP Q
CEP97|79598_CALCULATED -0.6785 4.464e-08 0.00107
DDB2|1643_CALCULATED -0.664 1.088e-07 0.0026
KPNA7|402569_CALCULATED 0.6639 1.09e-07 0.0026
ODZ4|26011|1OF2_CALCULATED -0.6561 1.731e-07 0.00413
FOXE1|2304_CALCULATED -0.6599 1.857e-07 0.00444
ST6GAL2|84620_CALCULATED -0.6588 1.982e-07 0.00474
TNNC2|7125_CALCULATED 0.653 2.069e-07 0.00494
LINC00173|100287569_CALCULATED -0.6474 2.841e-07 0.00678
RHBDL3|162494_CALCULATED -0.6416 3.902e-07 0.00932
C19ORF77|284422_CALCULATED 0.6404 4.181e-07 0.00999

Figure S1.  Get High-res Image As an example, this figure shows the association of CEP97|79598_CALCULATED to 'AGE'. P value = 4.46e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

3 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 1
  STAGE IA 3
  STAGE IB 2
  STAGE II 1
  STAGE IIA 16
  STAGE IIB 9
  STAGE III 5
  STAGE IIIA 6
  STAGE IIIB 5
  STAGE IIIC 1
  STAGE IV 1
     
  Significant markers N = 3
List of 3 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S5.  Get Full Table List of 3 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
CS330190|?|1OF2_CALCULATED 1.123e-113 2.68e-109
DQ600234|?_CALCULATED 5.273e-112 1.26e-107
DQ573774|?_CALCULATED 4.295e-84 1.03e-79

Figure S2.  Get High-res Image As an example, this figure shows the association of CS330190|?|1OF2_CALCULATED to 'NEOPLASM.DISEASESTAGE'. P value = 1.12e-113 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

13 genes related to 'PATHOLOGY.T.STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.54 (0.76)
  N
  1 6
  2 13
  3 29
  4 2
     
  Significant markers N = 13
  pos. correlated 0
  neg. correlated 13
List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S7.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
AX747838|?_CALCULATED -0.6977 1.795e-08 0.000429
LOC731275|731275_CALCULATED -0.6777 6.432e-08 0.00154
KDM6A|7403_CALCULATED -0.6639 1.471e-07 0.00351
MIR_584|?|5OF49_CALCULATED -0.7494 2.218e-07 0.0053
UNQ2790|?_CALCULATED -0.6447 4.356e-07 0.0104
INE1|8552_CALCULATED -0.6401 5.586e-07 0.0133
VPS54|51542_CALCULATED -0.639 5.904e-07 0.0141
CLCN5|1184_CALCULATED -0.6359 6.973e-07 0.0167
U6|?|158OF178_CALCULATED -0.6502 7.542e-07 0.018
RBP2|5948_CALCULATED -0.6456 1.266e-06 0.0302

Figure S3.  Get High-res Image As an example, this figure shows the association of AX747838|?_CALCULATED to 'PATHOLOGY.T.STAGE'. P value = 1.79e-08 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Mean (SD) 0.62 (0.78)
  N
  0 27
  1 16
  2 6
  3 1
     
  Significant markers N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

One gene related to 'PATHOLOGY.M.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 39
  M1A 1
  MX 6
     
  Significant markers N = 1
List of one gene differentially expressed by 'PATHOLOGY.M.STAGE'

Table S10.  Get Full Table List of one gene differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
TMEM132D|121256_CALCULATED 8.924e-08 0.00213

Figure S4.  Get High-res Image As an example, this figure shows the association of TMEM132D|121256_CALCULATED to 'PATHOLOGY.M.STAGE'. P value = 8.92e-08 with ANOVA analysis.

Clinical variable #7: 'GENDER'

16 genes related to 'GENDER'.

Table S11.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 7
  MALE 44
     
  Significant markers N = 16
  Higher in MALE 7
  Higher in FEMALE 9
List of top 10 genes differentially expressed by 'GENDER'

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

T(pos if higher in 'MALE') ttestP Q AUC
PRKY|5616_CALCULATED 21.38 6.039e-14 1.42e-09 1
EIF1AY|9086_CALCULATED 20.89 3.042e-11 7.13e-07 1
ANKRD5|63926_CALCULATED -7.76 4.894e-10 1.15e-05 0.8799
USP9Y|8287_CALCULATED 22.03 6.676e-10 1.56e-05 1
AK126491|?_CALCULATED 10.03 3.029e-09 7.1e-05 1
ZFY|7544_CALCULATED 22.08 7.671e-09 0.00018 1
DDX3Y|8653_CALCULATED 21.38 1.142e-08 0.000268 1
TSIX|9383_CALCULATED -11.75 1.67e-08 0.000391 0.9652
XIST|7503_CALCULATED -11.24 3.664e-08 0.000858 0.9679
MCM8|84515_CALCULATED -6.47 5.341e-08 0.00125 0.8929

Figure S5.  Get High-res Image As an example, this figure shows the association of PRKY|5616_CALCULATED to 'GENDER'. P value = 6.04e-14 with T-test analysis.

Clinical variable #8: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S13.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 35.62 (16)
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = ESCA-TP.mRNAseq_RPKM_log2.txt

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

  • Number of patients = 51

  • Number of genes = 23891

  • Number of clinical features = 8

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

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] 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)
Copyright © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle