Correlation between mRNAseq expression and clinical features

Pancreatic Adenocarcinoma (Primary solid tumor)

23 May 2013 | analyses__2013_05_23

Maintainer Information

Citation Information

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/C1S180JR

Overview

Introduction

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

Summary

Testing the association between 18603 genes and 7 clinical features across 18 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

9 genes correlated to 'GENDER'.

XIST|7503 , NLGN4Y|22829 , ZFY|7544 , RPS4Y1|6192 , UTY|7404 , ...

7 genes correlated to 'NEOPLASM.DISEASESTAGE'.

CCNT1|904 , ZC3HAV1L|92092 , TAF1L|138474 , ZNF192|7745 , UHMK1|127933 , ...

No genes correlated to 'AGE', 'DISTANT.METASTASIS', 'LYMPH.NODE.METASTASIS', 'COMPLETENESS.OF.RESECTION', and 'NUMBER.OF.LYMPH.NODES'.

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
AGE	Spearman correlation test	N=0
GENDER	t test	N=9	male	N=6	female	N=3
DISTANT METASTASIS	ANOVA test	N=0
LYMPH NODE METASTASIS	t test	N=0
COMPLETENESS OF RESECTION	ANOVA test	N=0
NUMBER OF LYMPH NODES	Spearman correlation test	N=0
NEOPLASM DISEASESTAGE	ANOVA test	N=7

Clinical variable #1: 'AGE'

No gene related to 'AGE'.

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


AGE	Mean (SD)	64.94 (8.4)
	Significant markers	N = 0

Clinical variable #2: 'GENDER'

9 genes related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	10
	MALE	8

	Significant markers	N = 9
	Higher in MALE	6
	Higher in FEMALE	3

List of 9 genes differentially expressed by 'GENDER'

Table S3. Get Full Table List of 9 genes differentially expressed by 'GENDER'

	T(pos if higher in 'MALE')	ttestP	Q	AUC
XIST\|7503	-27.05	1.384e-14	2.55e-10	1
NLGN4Y\|22829	27.25	9.312e-13	1.71e-08	1
ZFY\|7544	19.95	3.289e-10	6.06e-06	1
RPS4Y1\|6192	32.26	5.773e-10	1.06e-05	1
UTY\|7404	33.87	6.866e-10	1.26e-05	1
PRKY\|5616	13.28	1.188e-09	2.19e-05	1
DDX3Y\|8653	26.31	2.967e-09	5.46e-05	1
TSIX\|9383	-18.37	1.08e-08	0.000199	1
HDHD1A\|8226	-7.12	2.448e-06	0.0451	0.9875

Figure S1. Get High-res Image As an example, this figure shows the association of XIST|7503 to 'GENDER'. P value = 1.38e-14 with T-test analysis.

Clinical variable #3: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S4. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'


DISTANT.METASTASIS	Labels	N
	M0	3
	M1	1
	MX	14

	Significant markers	N = 0

Clinical variable #4: 'LYMPH.NODE.METASTASIS'

No gene related to 'LYMPH.NODE.METASTASIS'.

Table S5. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'


LYMPH.NODE.METASTASIS	Labels	N
	N0	8
	N1	10

	Significant markers	N = 0

Clinical variable #5: 'COMPLETENESS.OF.RESECTION'

No gene related to 'COMPLETENESS.OF.RESECTION'.

Table S6. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	13
	R1	4
	RX	1

	Significant markers	N = 0

Clinical variable #6: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S7. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'


NUMBER.OF.LYMPH.NODES	Mean (SD)	1.78 (2.7)
	Significant markers	N = 0

Clinical variable #7: 'NEOPLASM.DISEASESTAGE'

7 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S8. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE IA	2
	STAGE IB	1
	STAGE IIA	3
	STAGE IIB	10
	STAGE III	1
	STAGE IV	1

	Significant markers	N = 7

List of 7 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S9. Get Full Table List of 7 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

	ANOVA_P	Q
CCNT1\|904	1.572e-07	0.00292
ZC3HAV1L\|92092	1.662e-07	0.00309
TAF1L\|138474	3.862e-07	0.00718
ZNF192\|7745	5.154e-07	0.00958
UHMK1\|127933	5.479e-07	0.0102
ANKRD36BP1\|84832	7.551e-07	0.014
C19ORF56\|51398	2.182e-06	0.0406

Figure S2. Get High-res Image As an example, this figure shows the association of CCNT1|904 to 'NEOPLASM.DISEASESTAGE'. P value = 1.57e-07 with ANOVA analysis.

Methods & Data

Input

Expresson data file = PAAD-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
Clinical data file = PAAD-TP.clin.merged.picked.txt
Number of patients = 18
Number of genes = 18603
Number of clinical features = 7

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References

[1] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)

[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)

[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)

Made with Nozzle