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XGR (version 1.0.7)

Exploring Genomic Relations for Enhanced Interpretation Through Enrichment, Similarity, Network and Annotation Analysis

Description

The central goal of XGR is to provide a data interpretation system. It is designed to make a user-defined gene or SNP list (or genomic regions) more interpretable by comprehensively utilising ontology annotations and interaction networks to reveal relationships and enhance opportunities for biological discovery. XGR is unique in supporting a broad range of ontologies (including knowledge of biological and molecular functions, pathways, diseases and phenotypes - in both human and mouse) and different types of networks (including functional, physical and pathway interactions). There are two core functionalities of XGR. The first is to provide basic infrastructures for easy access to built-in ontologies and networks. The second is to support data interpretations via 1) enrichment analysis using either built-in or custom ontologies, 2) similarity analysis for calculating semantic similarity between genes (or SNPs) based on their ontology annotation profiles, 3) network analysis for identification of gene networks given a query list of (significant) genes, SNPs or genomic regions, and 4) annotation analysis for interpreting genomic regions using co-localised functional genomic annotations (such as open chromatin, epigenetic marks, TF binding sites and genomic segments) and using nearby gene annotations (by ontologies). Together with its web app, XGR aims to provide a user-friendly tool for exploring genomic relations at the gene, SNP and genomic region level.

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Version

Install

install.packages('XGR')

Monthly Downloads

23

Version

1.0.7

License

GPL-2

Homepage

http://XGR.r-forge.r-project.org

Maintainer

Hai Fang

Last Published

January 12th, 2017

Functions in XGR (1.0.7)

Function to convert an object between graph classes

Function to visualise enrichment results using a barplot

Function to define a colormap

Function to visualise a network as a circos plot

Function to calculate pair-wise semantic similarity between input terms based on a direct acyclic graph (DAG) with annotated data

Function to generate a subgraph of a direct acyclic graph (DAG) induced by the input annotation data

Function to check whether parallel computing should be used and how

Immune-disease associated variants, regions and genes from ImmunoBase (hg19)

Function to compare enrichment results using side-by-side barplots

Table S2A for cis-eQTLs among shared datasets from Benjamin et al. (2014)

Function to view enrichment results

xEnrichConciser

Function to make enrichment results conciser by removing redundant terms

Function to assign (and evaluate) arguments with default values for a given function

Function to conduct enrichment analysis given the input data and the ontology and its annotation

Function to visualise enrichment results using a direct acyclic graph (DAG)

xEnrichDAGplotAdv

Function to visualise comparative enrichment results using a direct acyclic graph (DAG)

Function to conduct enrichment analysis given a list of genes and the ontology in query

Function to conduct enrichment analysis given YOUR own input data

Function to conduct enrichment analysis given a list of SNPs and the ontology in query

Function to visualise enrichment results using different network layouts

Function to conduct region-based enrichment analysis using nearby gene annotations

Function to create a GRanges object given a list of genomic regions

Function to score genomic regions based on the given significance level

Function to score lead or LD SNPs based on the given significance level

Function to identify likely modulated seed genes given a list of genomic regions together with the significance level

Function to calculate pair-wise semantic similarity given the input data and the ontology and its annotation

Function to extract genomic locations given a list of SNPs

Function to define nearby genes given a list of SNPs

xSocialiserSNPs

Function to calculate pair-wise semantic similarity given a list of SNPs and the ontology in query

Function to create a sparse matrix for an input file with three columns

Function to lift genomic intervals from one genome build to another.

Function to wrap texts from Rd files

Function to load the package built-in RData

Function to convert Rd files to HTML files

Function to identify a gene network from an input network given a list of seed SNPs together with the significance level (e.g. GWAS reported p-values)

Function to visualise distance kernel functions

xGRviaGenomicAnnoAdv

Function to conduct region-based enrichment analysis using genomic annotations via sampling

xGRviaGenomicAnno

Function to conduct region-based enrichment analysis using genomic annotations via binomial test

Function to generate random samples for data genomic regions from background genomic regions

Function to define nearby genes given a list of genomic regions

Function to create a data frame (with three columns) from a (sparse) matrix

Function to identify a subnetwork from an input network and the signficance level imposed on its nodes

xSNP2GeneScores

Function to identify likely modulated seed genes given a list of SNPs together with the significance level (e.g. GWAS reported p-values)

Function to visualise a graph object of class "igraph"

xSocialiserDAGplotAdv

Function to draw DAG plot for comparing two sets of terms used to annotate two SNPs or genes in query

Function to identify a gene network from an input network given a list of genomic regions together with the significance level

xSocialiserGenes

Function to calculate pair-wise semantic similarity given a list of genes and the ontology in query

xSocialiserDAGplot

Function to draw DAG plot for visualising terms used to annotate an input SNP or gene

xSocialiserNetplot

Function to visualise terms used to annotate an input SNP or gene using different network layouts