Correlation between mRNAseq expression and clinical features

Esophageal Carcinoma (Primary solid tumor)

17 October 2014 | analyses__2014_10_17

Maintainer Information

Citation Information

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/C12V2F0F

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 23512 genes and 9 clinical features across 108 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one genes.

80 genes correlated to 'AGE'.

RIPK3|11035_CALCULATED , CBX1|10951_CALCULATED , SIX1|6495_CALCULATED , MCM2|4171_CALCULATED , KIF3C|3797_CALCULATED , ...

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

R3HDML|140902_CALCULATED , RAP1GAP2|23108_CALCULATED , NHSL1|57224_CALCULATED , TNFRSF11A|8792_CALCULATED , PLEKHG6|55200_CALCULATED , ...

1 gene correlated to 'GENDER'.

TXLNG2P|246126_CALCULATED

1109 genes correlated to 'RACE'.

RNF217|154214_CALCULATED , TMC5|79838_CALCULATED , HAP1|9001_CALCULATED , TMTC3|160418_CALCULATED , ALOX12P2|245_CALCULATED , ...

No genes correlated to 'Time to Death', 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.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 P value < 0.05 and Q value < 0.3.

Clinical feature	Statistical test	Significant genes	Associated with		Associated with
Time to Death	Cox regression test	N=0
AGE	Spearman correlation test	N=80	older	N=14	younger	N=66
NEOPLASM DISEASESTAGE	Kruskal-Wallis test	N=0
PATHOLOGY T STAGE	Spearman correlation test	N=13	higher stage	N=1	lower stage	N=12
PATHOLOGY N STAGE	Spearman correlation test	N=0
PATHOLOGY M STAGE	Kruskal-Wallis test	N=0
GENDER	Wilcoxon test	N=1	male	N=1	female	N=0
NUMBERPACKYEARSSMOKED	Spearman correlation test	N=0
RACE	Wilcoxon test	N=1109	white	N=1109	asian	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)	0-122.1 (median=4.9)
	censored	N = 67
	death	N = 34

	Significant markers	N = 0

Clinical variable #2: 'AGE'

80 genes related to 'AGE'.

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


AGE	Mean (SD)	62.52 (12)
	Significant markers	N = 80
	pos. correlated	14
	neg. correlated	66

List of top 10 genes differentially expressed by 'AGE'

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

	SpearmanCorr	corrP	Q
RIPK3\|11035_CALCULATED	0.4809	1.378e-07	0.00324
CBX1\|10951_CALCULATED	-0.4763	1.889e-07	0.00444
SIX1\|6495_CALCULATED	-0.4759	1.934e-07	0.00455
MCM2\|4171_CALCULATED	-0.4747	2.094e-07	0.00492
KIF3C\|3797_CALCULATED	-0.4625	4.66e-07	0.011
TMC5\|79838_CALCULATED	0.4622	4.776e-07	0.0112
CDC7\|8317_CALCULATED	-0.4596	5.625e-07	0.0132
HIST1H2BO\|8348_CALCULATED	-0.4571	7.448e-07	0.0175
WDHD1\|11169_CALCULATED	-0.4519	9.16e-07	0.0215
MCM5\|4174_CALCULATED	-0.4517	9.282e-07	0.0218

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

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


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	7
	STAGE IA	4
	STAGE IB	4
	STAGE II	1
	STAGE IIA	30
	STAGE IIB	17
	STAGE III	11
	STAGE IIIA	8
	STAGE IIIB	7
	STAGE IIIC	3
	STAGE IV	2

	Significant markers	N = 0

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

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

Table S5. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'


PATHOLOGY.T.STAGE	Mean (SD)	2.35 (0.86)
		N
	0	1
	1	19
	2	26
	3	49
	4	3

	Significant markers	N = 13
	pos. correlated	1
	neg. correlated	12

List of top 10 genes differentially expressed by 'PATHOLOGY.T.STAGE'

Table S6. Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
R3HDML\|140902_CALCULATED	-0.6038	1.342e-06	0.0315
RAP1GAP2\|23108_CALCULATED	-0.4539	2.676e-06	0.0629
NHSL1\|57224_CALCULATED	-0.4508	3.19e-06	0.075
TNFRSF11A\|8792_CALCULATED	-0.443	4.934e-06	0.116
PLEKHG6\|55200_CALCULATED	-0.4417	5.293e-06	0.124
DDIT4L\|115265_CALCULATED	0.4435	5.369e-06	0.126
SEC16B\|89866_CALCULATED	-0.4387	6.236e-06	0.147
CPT1A\|1374_CALCULATED	-0.4358	7.271e-06	0.171
ACOT11\|26027_CALCULATED	-0.4341	7.998e-06	0.188
PLCB3\|5331_CALCULATED	-0.4313	9.256e-06	0.218

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

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

Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'


PATHOLOGY.N.STAGE	Mean (SD)	0.63 (0.78)
		N
	0	51
	1	34
	2	9
	3	3

	Significant markers	N = 0

Clinical variable #6: 'PATHOLOGY.M.STAGE'

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

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


PATHOLOGY.M.STAGE	Labels	N
	M0	77
	M1	1
	M1A	1
	MX	15

	Significant markers	N = 0

Clinical variable #7: 'GENDER'

One gene related to 'GENDER'.

Table S9. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	16
	MALE	92

	Significant markers	N = 1
	Higher in MALE	1
	Higher in FEMALE	0

List of one gene differentially expressed by 'GENDER'

Table S10. Get Full Table List of one gene differentially expressed by 'GENDER'. 9 significant gene(s) located in sex chromosomes is(are) filtered out.

	W(pos if higher in 'MALE')	wilcoxontestP	Q	AUC
TXLNG2P\|246126_CALCULATED	644	1.14e-05	0.268	1

Clinical variable #8: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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


NUMBERPACKYEARSSMOKED	Mean (SD)	35.68 (20)
	Significant markers	N = 0

Clinical variable #9: 'RACE'

1109 genes related to 'RACE'.

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


RACE	Labels	N
	ASIAN	36
	WHITE	68

	Significant markers	N = 1109
	Higher in WHITE	1109
	Higher in ASIAN	0

List of top 10 genes differentially expressed by 'RACE'

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

	W(pos if higher in 'WHITE')	wilcoxontestP	Q	AUC
RNF217\|154214_CALCULATED	259	4.394e-11	1.03e-06	0.8942
TMC5\|79838_CALCULATED	2185	5.28e-11	1.24e-06	0.8926
HAP1\|9001_CALCULATED	270	9.771e-11	2.3e-06	0.8881
TMTC3\|160418_CALCULATED	283	1.309e-10	3.08e-06	0.8844
ALOX12P2\|245_CALCULATED	284.5	1.399e-10	3.29e-06	0.8838
TSPAN8\|7103_CALCULATED	2081.5	1.513e-10	3.56e-06	0.8876
STL\|7955_CALCULATED	288	1.635e-10	3.84e-06	0.8824
KLRG2\|346689_CALCULATED	247	2.135e-10	5.02e-06	0.8875
LRP12\|29967_CALCULATED	300	2.791e-10	6.56e-06	0.8775
CAGE1\|285782_CALCULATED	295	2.992e-10	7.03e-06	0.8777

Methods & Data

Input

Expresson data file = ESCA-TP.mRNAseq_RPKM_log2.txt
Clinical data file = ESCA-TP.merged_data.txt
Number of patients = 108
Number of genes = 23512
Number of clinical features = 9

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)

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