Correlation between miRseq expression and clinical features

Rectum 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 miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1N014M2

Overview

Introduction

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

Summary

Testing the association between 427 genes and 10 clinical features across 143 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.

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

HSA-MIR-514-2

2 genes correlated to 'LYMPH.NODE.METASTASIS'.

HSA-MIR-372 , HSA-MIR-624

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

HSA-MIR-361

No genes correlated to 'Time to Death', 'AGE', 'GENDER', 'HISTOLOGICAL.TYPE', 'DISTANT.METASTASIS', 'NUMBER.OF.LYMPH.NODES', and 'NEOPLASM.DISEASESTAGE'.

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
GENDER	t test	N=0
HISTOLOGICAL TYPE	t test	N=0
RADIATIONS RADIATION REGIMENINDICATION	t test	N=1	yes	N=1	no	N=0
DISTANT METASTASIS	ANOVA test	N=0
LYMPH NODE METASTASIS	ANOVA test	N=2
COMPLETENESS OF RESECTION	ANOVA test	N=1
NUMBER OF LYMPH NODES	Spearman correlation test	N=0
NEOPLASM DISEASESTAGE	ANOVA 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)	0.2-121.1 (median=7)
	censored	N = 101
	death	N = 10

	Significant markers	N = 0

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

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


AGE	Mean (SD)	65.39 (12)
	Significant markers	N = 0

Clinical variable #3: 'GENDER'

No gene related to 'GENDER'.

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


GENDER	Labels	N
	FEMALE	66
	MALE	77

	Significant markers	N = 0

Clinical variable #4: 'HISTOLOGICAL.TYPE'

No gene related to 'HISTOLOGICAL.TYPE'.

Table S4. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	RECTAL ADENOCARCINOMA	127
	RECTAL MUCINOUS ADENOCARCINOMA	10

	Significant markers	N = 0

Clinical variable #5: 'RADIATIONS.RADIATION.REGIMENINDICATION'

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

Table S5. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	6
	YES	137

	Significant markers	N = 1
	Higher in YES	1
	Higher in NO	0

List of one gene differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S6. Get Full Table List of one gene differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

	T(pos if higher in 'YES')	ttestP	Q	AUC
HSA-MIR-514-2	5.99	0.000117	0.0478	0.8902

Figure S1. Get High-res Image As an example, this figure shows the association of HSA-MIR-514-2 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 0.000117 with T-test analysis.

Clinical variable #6: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S7. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'


DISTANT.METASTASIS	Labels	N
	M0	107
	M1	18
	M1A	2
	MX	14

	Significant markers	N = 0

Clinical variable #7: 'LYMPH.NODE.METASTASIS'

2 genes related to 'LYMPH.NODE.METASTASIS'.

Table S8. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'


LYMPH.NODE.METASTASIS	Labels	N
	N0	74
	N1	30
	N1A	4
	N1B	3
	N1C	1
	N2	21
	N2A	2
	N2B	5
	NX	2

	Significant markers	N = 2

List of 2 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S9. Get Full Table List of 2 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

	ANOVA_P	Q
HSA-MIR-372	3.8e-08	1.62e-05
HSA-MIR-624	2.297e-05	0.00979

Figure S2. Get High-res Image As an example, this figure shows the association of HSA-MIR-372 to 'LYMPH.NODE.METASTASIS'. P value = 3.8e-08 with ANOVA analysis.

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

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

Table S10. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	102
	R1	2
	R2	11
	RX	3

	Significant markers	N = 1

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

Table S11. Get Full Table List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'

	ANOVA_P	Q
HSA-MIR-361	5.259e-05	0.0225

Figure S3. Get High-res Image As an example, this figure shows the association of HSA-MIR-361 to 'COMPLETENESS.OF.RESECTION'. P value = 5.26e-05 with ANOVA analysis.

Clinical variable #9: 'NUMBER.OF.LYMPH.NODES'

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

Table S12. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'


NUMBER.OF.LYMPH.NODES	Mean (SD)	2.58 (5.3)
	Significant markers	N = 0

Clinical variable #10: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S13. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	28
	STAGE II	8
	STAGE IIA	33
	STAGE IIB	2
	STAGE IIC	1
	STAGE III	6
	STAGE IIIA	5
	STAGE IIIB	20
	STAGE IIIC	12
	STAGE IV	14
	STAGE IVA	7

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = READ-TP.miRseq_RPKM_log2.txt
Clinical data file = READ-TP.clin.merged.picked.txt
Number of patients = 143
Number of genes = 427
Number of clinical features = 10

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

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] 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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