Significant over-representation of pathway gene sets for a given gene list
Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C14J0DHH
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Significant over-representation of pathway gene sets for a given gene list. Broad Institute of MIT and Harvard. doi:10.7908/C14J0DHH
Overview
Introduction

This pipeline inspects significant overlapping pathway gene sets for a given gene list using a hypergeometric test. For the gene set database, we uses GSEA MSigDB Class2: Canonical Pathways DB as a gene set data. Further details about the MsigDB gene sets, please visit The Broad Institute GSEA MsigDB

Summary

For a given gene list, a hypergeometric test was tried to find significant overlapping canonical pathways using 1320 gene sets. In terms of FDR adjusted p.values, top 5 significant overlapping gene sets are listed as below.

  • REACTOME_IMMUNE_SYSTEM, REACTOME_CYTOKINE_SIGNALING_IN_IMMUNE_SYSTEM, REACTOME_INTERFERON_GAMMA_SIGNALING, REACTOME_INTERFERON_SIGNALING, REACTOME_ENDOSOMAL_VACUOLAR_PATHWAY

Results
For a given gene list, top significant overlapping canonical pathway gene sets

Table 1.  Get Full Table This table shows significant gene sets in which at least one gene is found and its FDR adjusted p.value is smaller than 0.3. the hypergeometric p-value is a probability of randomly drawing x or more successes(gene overlaps in gene set database) from the population (gene universe consisting of N number of genes) in k total draws(the number of input genes). The hypergeometric test is identical to the corresponding one-tailed version of Fisher's exact test. That is, P(X=x) = f(x| N,m,k). The FDR q.value was obtained for 1320 multiple comparison.

GS(gene set) pathway name gene.list GS size (m) n.NotInGS (n) Gene universe (N) n.drawn (k) n.found (x) p.value (p(X>=x)) FDR (q.value)
REACTOME IMMUNE SYSTEM gene.list 933 45023 45956 41 13 9.556e-13 1.261e-09
REACTOME CYTOKINE SIGNALING IN IMMUNE SYSTEM gene.list 270 45686 45956 41 8 1.034e-10 6.823e-08
REACTOME INTERFERON GAMMA SIGNALING gene.list 63 45893 45956 41 5 2.970e-09 1.307e-06
REACTOME INTERFERON SIGNALING gene.list 159 45797 45956 41 6 6.346e-09 2.094e-06
REACTOME ENDOSOMAL VACUOLAR PATHWAY gene.list 9 45947 45956 41 3 5.515e-08 1.456e-05
REACTOME INTERFERON ALPHA BETA SIGNALING gene.list 64 45892 45956 41 4 3.331e-07 7.329e-05
REACTOME ADAPTIVE IMMUNE SYSTEM gene.list 539 45417 45956 41 7 4.675e-07 8.816e-05
REACTOME ANTIGEN PRESENTATION FOLDING ASSEMBLY AND PEPTIDE LOADING OF CLASS I MHC gene.list 21 45935 45956 41 3 8.668e-07 1.430e-04
KEGG ANTIGEN PROCESSING AND PRESENTATION gene.list 89 45867 45956 41 4 1.260e-06 1.848e-04
KEGG ALLOGRAFT REJECTION gene.list 38 45918 45956 41 3 5.440e-06 7.181e-04
KEGG GRAFT VERSUS HOST DISEASE gene.list 42 45914 45956 41 3 7.385e-06 8.862e-04
KEGG TYPE I DIABETES MELLITUS gene.list 44 45912 45956 41 3 8.509e-06 9.360e-04
KEGG AUTOIMMUNE THYROID DISEASE gene.list 53 45903 45956 41 3 1.497e-05 1.520e-03
REACTOME ER PHAGOSOME PATHWAY gene.list 61 45895 45956 41 3 2.288e-05 2.157e-03
ST FAS SIGNALING PATHWAY gene.list 65 45891 45956 41 3 2.770e-05 2.438e-03
REACTOME IMMUNOREGULATORY INTERACTIONS BETWEEN A LYMPHOID AND A NON LYMPHOID CELL gene.list 70 45886 45956 41 3 3.461e-05 2.855e-03
KEGG B CELL RECEPTOR SIGNALING PATHWAY gene.list 75 45881 45956 41 3 4.256e-05 3.247e-03
REACTOME ANTIGEN PROCESSING CROSS PRESENTATION gene.list 76 45880 45956 41 3 4.428e-05 3.247e-03
KEGG APOPTOSIS gene.list 88 45868 45956 41 3 6.861e-05 4.767e-03
REACTOME CLASS I MHC MEDIATED ANTIGEN PROCESSING PRESENTATION gene.list 251 45705 45956 41 4 7.506e-05 4.954e-03

Figure 1.  Get High-res Image This figure is an event heatmap indicating gene matches across gene sets

Methods & Data
Input

  • Gene set database = c2.cp.v4.0.symbols.gmt

Hypergeometric Test

For a given gene list, it uses a hypergeometric test to get a significance of each overlapping pathway gene set. The hypergeometric p-value is obtained by R library function phyper() and is defined as a probability of randomly drawing x or more successes(gene matches) from the population consisting N genes in k(the input genes) total draws.

  • a cumulative p-value using the R function phyper():

    • ex). a probability to see at least x genes in the group is defined as p(X>=x) = 1 - p(X<=x)= 1 - phyper(x-1, m, n, k, lower.tail=FALSE, log.p=FALSE) that is, f(x| N, m, k) = (m) C (k) * ((N-m) C (n-k)) / ((N) C (n))

  • The hypergeometric test is identical to the corresponding one-tailed version of Fisher's exact test.

    • ex). Fisher' exact test = matrix(c(n.Found, n.GS-n.Found, n.drawn-n.Found, n.NotGS- (n.drawn-n.Found)), nrow=2, dimnames = list(inputGenes = c("Found", "NotFound"),GeneUniverse = c("GS", "nonGS")) )

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] Johnson, N.L., et al, Univariate Discrete Distributions, Second Edition, Wiley (1992)
[2] Berkopec, Aleš, HyperQuick algorithm for discrete hypergeometric distribution, Journal of Discrete Algorithms:341-347 (2007)
[3] Tamayo, et al, Molecular Signatures Database, MSigDB, PNAS:15545-15550 (2005)
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