Pi: Leveraging Genetic Evidence to Prioritise Drug Targets at the Gene, Pathway and Network Level

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Priority index or Pi is developed as a genomic-led target prioritisation system, with the focus on leveraging human genetic data to prioritise potential drug targets at the gene, pathway and network level. The long term goal is to use such information to enhance early-stage target validation. Based on evidence of disease association from genome-wide association studies (GWAS), this prioritisation system is able to generate evidence to support identification of the specific modulated genes (seed genes) that are responsible for the genetic association signal by utilising knowledge of linkage disequilibrium (co-inherited genetic variants), distance of associated variants from the gene, evidence of independent genetic association with gene expression in disease-relevant tissues, cell types and states, and evidence of physical interactions between disease-associated genetic variants and gene promoters based on genome-wide capture HiC-generated promoter interactomes in primary blood cell types. Seed genes are scored in an integrative way, quantifying the genetic influence. Scored seed genes are subsequently used as baits to rank seed genes plus additional (non-seed) genes; this is achieved by iteratively exploring the global connectivity of a gene interaction network. Genes with the highest priority are further used to identify/prioritise pathways that are significantly enriched with highly prioritised genes. Prioritised genes are also used to identify a gene network interconnecting highly prioritised genes and a minimal number of less prioritised genes (which act as linkers bringing together highly prioritised genes).

Author
Hai Fang, the ULTRA-DD Consortium, Julian C Knight
Date of publication
2016-12-05 09:37:08
Maintainer
Hai Fang <hfang@well.ox.ac.uk>
License
GPL-3
Version
1.1.1
URLs

View on R-Forge

Man pages

xContour
Function to visualise a numeric matrix as a contour plot
xPCHiCplot
Function to visualise promoter capture HiC data using...
xPier
Function to do prioritisation through random walk techniques
xPierGenes
Function to priorise genes from an input network and the...
xPierManhattan
Function to visualise prioritised genes using manhattan plot
xPierMatrix
Function to extract priority matrix from a list of pNode...
xPierPathways
Function to prioritise pathways based on enrichment analysis...
xPierSNPs
Function to priorise genes given a list of seed SNPs together...
xPierSNPsConsensus
Function to resolve relative importance of distance weight...
xPierSubnet
Function to identify a gene network from top prioritised...
xPredictCompare
Function to compare prediction performance results
xPredictPR
Function to assess the prediction performance via...
xPredictROCR
Function to assess the prediction performance via ROC and...
xRWR
Function to implement Random Walk with Restart (RWR) on the...
xSNP2cGenes
Function to define HiC genes given a list of SNPs
xSNP2eGenes
Function to define eQTL genes given a list of SNPs or a...
xSNPeqtl
Function to extract eQTL-gene pairs given a list of SNPs or a...
xSNPhic
Function to extract promoter capture HiC-gene pairs given a...

Files in this package

Pi/DESCRIPTION
Pi/NAMESPACE
Pi/R
Pi/R/xContour.r
Pi/R/xPCHiCplot.r
Pi/R/xPier.r
Pi/R/xPierGenes.r
Pi/R/xPierManhattan.r
Pi/R/xPierMatrix.r
Pi/R/xPierPathways.r
Pi/R/xPierSNPs.r
Pi/R/xPierSNPsConsensus.r
Pi/R/xPierSubnet.r
Pi/R/xPredictCompare.r
Pi/R/xPredictROCR.r
Pi/R/xRWR.r
Pi/R/xSNP2cGenes.r
Pi/R/xSNP2eGenes.r
Pi/R/xSNPeqtl.r
Pi/R/xSNPhic.r
Pi/build
Pi/build/vignette.rds
Pi/inst
Pi/inst/CITATION
Pi/inst/NEWS
Pi/inst/Pi.icon.png
Pi/inst/Pi.logo.png
Pi/inst/doc
Pi/inst/doc/Pi_vignettes.Rmd
Pi/inst/doc/Pi_vignettes.html
Pi/inst/xContour.html
Pi/inst/xPCHiCplot.html
Pi/inst/xPier.html
Pi/inst/xPierGenes.html
Pi/inst/xPierManhattan.html
Pi/inst/xPierMatrix.html
Pi/inst/xPierPathways.html
Pi/inst/xPierSNPs.html
Pi/inst/xPierSNPsConsensus.html
Pi/inst/xPierSubnet.html
Pi/inst/xPredictCompare.html
Pi/inst/xPredictPR.html
Pi/inst/xPredictROCR.html
Pi/inst/xRWR.html
Pi/inst/xSNP2cGenes.html
Pi/inst/xSNP2eGenes.html
Pi/inst/xSNPeqtl.html
Pi/inst/xSNPhic.html
Pi/man
Pi/man/xContour.Rd
Pi/man/xPCHiCplot.Rd
Pi/man/xPier.Rd
Pi/man/xPierGenes.Rd
Pi/man/xPierManhattan.Rd
Pi/man/xPierMatrix.Rd
Pi/man/xPierPathways.Rd
Pi/man/xPierSNPs.Rd
Pi/man/xPierSNPsConsensus.Rd
Pi/man/xPierSubnet.Rd
Pi/man/xPredictCompare.Rd
Pi/man/xPredictPR.Rd
Pi/man/xPredictROCR.Rd
Pi/man/xRWR.Rd
Pi/man/xSNP2cGenes.Rd
Pi/man/xSNP2eGenes.Rd
Pi/man/xSNPeqtl.Rd
Pi/man/xSNPhic.Rd
Pi/vignettes
Pi/vignettes/Pi_vignettes.Rmd
Pi/vignettes/now.Pi.bib
Pi/vignettes/saved.Pi.functions.old.png
Pi/vignettes/saved.Pi.functions.png
Pi/vignettes/saved.Pi.gene_manhattan.png
Pi/vignettes/saved.Pi.network_vis.png
Pi/vignettes/saved.Pi.pathway_barplot.png
Pi/vignettes/saved.Pi.workflow.old.png
Pi/vignettes/saved.Pi.workflow.png