Package: GIGSEA 1.25.0

Shijia Zhu

GIGSEA: Genotype Imputed Gene Set Enrichment Analysis

We presented the Genotype-imputed Gene Set Enrichment Analysis (GIGSEA), a novel method that uses GWAS-and-eQTL-imputed trait-associated differential gene expression to interrogate gene set enrichment for the trait-associated SNPs. By incorporating eQTL from large gene expression studies, e.g. GTEx, GIGSEA appropriately addresses such challenges for SNP enrichment as gene size, gene boundary, SNP distal regulation, and multiple-marker regulation. The weighted linear regression model, taking as weights both imputation accuracy and model completeness, was used to perform the enrichment test, properly adjusting the bias due to redundancy in different gene sets. The permutation test, furthermore, is used to evaluate the significance of enrichment, whose efficiency can be largely elevated by expressing the computational intensive part in terms of large matrix operation. We have shown the appropriate type I error rates for GIGSEA (<5%), and the preliminary results also demonstrate its good performance to uncover the real signal.

Authors:Shijia Zhu

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NEWS

# Install 'GIGSEA' in R:
install.packages('GIGSEA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On BioConductor:GIGSEA-1.25.0(bioc 3.21)GIGSEA-1.24.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

genesetenrichmentsnpvariantannotationgeneexpressiongeneregulationregressiondifferentialexpression

4.30 score 2 scripts 127 downloads 2 mentions 14 exports 4 dependencies

Last updated 2 months agofrom:af5e89ca4e. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 29 2024
R-4.5-winOKNov 29 2024
R-4.5-linuxOKNov 29 2024
R-4.4-winOKNov 29 2024
R-4.4-macOKNov 29 2024
R-4.3-winOKNov 29 2024
R-4.3-macOKNov 29 2024

Exports:dataframe2geneSetgeneSet2NetgeneSet2sparseMatrixgmt2geneSetmatrixPvalorderedIntersectpermutationMultipleLmpermutationMultipleLmMatrixpermutationSimpleLmpermutationSimpleLmMatrixrunGIGSEAweightedGSEAweightedMultipleLmweightedPearsonCorr

Dependencies:latticelocfdrMASSMatrix

GIGSEA: Genotype Imputed Gene Set Enrichment Analysis

Rendered fromGIGSEA_tutorial.Rmdusingknitr::rmarkdownon Nov 29 2024.

Last update: 2018-05-29
Started: 2017-09-03

Readme and manuals

Help Manual

Help pageTopics
dataframe2geneSetdataframe2geneSet
geneSet2NetgeneSet2Net
geneSet2sparseMatrixgeneSet2sparseMatrix
gmt2geneSetgmt2geneSet
heart.metaXcanheart.metaXcan
matrixPvalmatrixPval
MSigDB.KEGG.PathwayMSigDB.KEGG.Pathway
MSigDB.miRNAMSigDB.miRNA
MSigDB.TFMSigDB.TF
orderedIntersectorderedIntersect
permutationMultipleLmpermutationMultipleLm
permutationMultipleLmMatrixpermutationMultipleLmMatrix
permutationSimpleLmpermutationSimpleLm
permutationSimpleLmMatrixpermutationSimpleLmMatrix
runGIGSEArunGIGSEA
TargetScan.miRNATargetScan.miRNA
weightedGSEAweightedGSEA
weightedMultipleLmweightedMultipleLm
weightedPearsonCorrweightedPearsonCorr