Correlation between mRNAseq expression and clinical features

Liver Hepatocellular Carcinoma (Primary solid tumor)

15 January 2014 | analyses__2014_01_15

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/C1RR1WPK

Overview

Introduction

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

Summary

Testing the association between 17802 genes and 8 clinical features across 124 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

5 genes correlated to 'NEOPLASM.DISEASESTAGE'.

KCNT1|57582 , THNSL2|55258 , DPYS|1807 , LOC399815|399815 , DPH1|1801

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

TFAP2A|7020 , POLA2|23649 , RNF123|63891 , CARKD|55739

33 genes correlated to 'PATHOLOGY.N.STAGE'.

PI4KAP2|375133 , AGPAT2|10555 , PRSS35|167681 , ATP5F1|515 , WARS2|10352 , ...

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

KCNT1|57582

34 genes correlated to 'GENDER'.

XIST|7503 , RPS4Y1|6192 , ZFY|7544 , TSIX|9383 , PRKY|5616 , ...

1 gene correlated to 'COMPLETENESS.OF.RESECTION'.

PGA5|5222

No genes correlated to 'Time to Death', and 'AGE'.

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=0
NEOPLASM DISEASESTAGE	ANOVA test	N=5
PATHOLOGY T STAGE	Spearman correlation test	N=4	higher stage	N=2	lower stage	N=2
PATHOLOGY N STAGE	t test	N=33	class1	N=24	class0	N=9
PATHOLOGY M STAGE	ANOVA test	N=1
GENDER	t test	N=34	male	N=14	female	N=20
COMPLETENESS OF RESECTION	ANOVA test	N=1

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)	0-113 (median=14.3)
	censored	N = 67
	death	N = 53

	Significant markers	N = 0

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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


AGE	Mean (SD)	61.55 (14)
	Significant markers	N = 0

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

5 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S3. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	47
	STAGE II	27
	STAGE III	2
	STAGE IIIA	29
	STAGE IIIB	2
	STAGE IIIC	5
	STAGE IV	1
	STAGE IVA	1
	STAGE IVB	1

	Significant markers	N = 5

List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S4. Get Full Table List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

	ANOVA_P	Q
KCNT1\|57582	1.733e-08	0.000309
THNSL2\|55258	3.705e-07	0.0066
DPYS\|1807	1.313e-06	0.0234
LOC399815\|399815	1.745e-06	0.0311
DPH1\|1801	2.536e-06	0.0451

Figure S1. Get High-res Image As an example, this figure shows the association of KCNT1|57582 to 'NEOPLASM.DISEASESTAGE'. P value = 1.73e-08 with ANOVA analysis.

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

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

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


PATHOLOGY.T.STAGE	Mean (SD)	2.01 (0.97)
		N
	1	50
	2	30
	3	37
	4	7

	Significant markers	N = 4
	pos. correlated	2
	neg. correlated	2

List of 4 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S6. Get Full Table List of 4 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
TFAP2A\|7020	0.4348	6.958e-07	0.0124
POLA2\|23649	0.4224	1.027e-06	0.0183
RNF123\|63891	-0.4177	1.385e-06	0.0246
CARKD\|55739	-0.4107	2.159e-06	0.0384

Figure S2. Get High-res Image As an example, this figure shows the association of TFAP2A|7020 to 'PATHOLOGY.T.STAGE'. P value = 6.96e-07 with Spearman correlation analysis.

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

33 genes related to 'PATHOLOGY.N.STAGE'.

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


PATHOLOGY.N.STAGE	Labels	N
	class0	80
	class1	3

	Significant markers	N = 33
	Higher in class1	24
	Higher in class0	9

List of top 10 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S8. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.N.STAGE'

	T(pos if higher in 'class1')	ttestP	Q	AUC
PI4KAP2\|375133	9.36	1.24e-10	1.98e-06	0.9083
AGPAT2\|10555	7.38	1.244e-10	1.98e-06	0.8125
PRSS35\|167681	-8.06	2.395e-10	3.81e-06	0.859
ATP5F1\|515	7.22	4.032e-10	6.42e-06	0.8042
WARS2\|10352	9.2	5.19e-10	8.26e-06	0.9083
STAB2\|55576	-7.24	1.877e-09	2.99e-05	0.801
ARMCX3\|51566	7.33	4.673e-09	7.44e-05	0.7917
SFRS6\|6431	7.02	1.063e-08	0.000169	0.7917
WNT5A\|7474	6.89	1.355e-08	0.000216	0.7958
LRRC1\|55227	6.67	1.8e-08	0.000286	0.8042

Figure S3. Get High-res Image As an example, this figure shows the association of PI4KAP2|375133 to 'PATHOLOGY.N.STAGE'. P value = 1.24e-10 with T-test analysis.

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	97
	M1	2
	MX	25

	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
KCNT1\|57582	8.041e-11	1.43e-06

Figure S4. Get High-res Image As an example, this figure shows the association of KCNT1|57582 to 'PATHOLOGY.M.STAGE'. P value = 8.04e-11 with ANOVA analysis.

Clinical variable #7: 'GENDER'

34 genes related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	47
	MALE	77

	Significant markers	N = 34
	Higher in MALE	14
	Higher in FEMALE	20

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
XIST\|7503	-14.01	2.482e-24	4.42e-20	0.9648
RPS4Y1\|6192	22.85	2.775e-21	4.94e-17	0.9966
ZFY\|7544	21.32	2.136e-19	3.8e-15	0.9952
TSIX\|9383	-12.66	1.208e-17	2.15e-13	0.9695
PRKY\|5616	17.14	2.323e-17	4.13e-13	0.9938
DDX3Y\|8653	20.66	1.586e-15	2.82e-11	0.9986
NLGN4Y\|22829	15.1	2.677e-15	4.76e-11	0.9877
KDM5D\|8284	18.91	2.825e-14	5.03e-10	0.9968
KDM5C\|8242	-7.39	3.731e-11	6.64e-07	0.832
BMP8B\|656	-6.34	7.79e-09	0.000139	0.7983

Figure S5. Get High-res Image As an example, this figure shows the association of XIST|7503 to 'GENDER'. P value = 2.48e-24 with T-test analysis.

Clinical variable #8: 'COMPLETENESS.OF.RESECTION'

One gene related to 'COMPLETENESS.OF.RESECTION'.

Table S13. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	100
	R1	10
	R2	1
	RX	8

	Significant markers	N = 1

List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S14. Get Full Table List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

	ANOVA_P	Q
PGA5\|5222	1.751e-06	0.0312

Figure S6. Get High-res Image As an example, this figure shows the association of PGA5|5222 to 'COMPLETENESS.OF.RESECTION'. P value = 1.75e-06 with ANOVA analysis.

Methods & Data

Input

Expresson data file = LIHC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
Clinical data file = LIHC-TP.merged_data.txt
Number of patients = 124
Number of genes = 17802
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)

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