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HTSanalyzeR (version 2.20.0)

Gene set over-representation, enrichment and network analyses for high-throughput screens

Description

This package provides classes and methods for gene set over-representation, enrichment and network analyses on high-throughput screens. The over-representation analysis is performed based on hypergeometric tests. The enrichment analysis is based on the GSEA algorithm (Subramanian et al. PNAS 2005). The network analysis identifies enriched subnetworks based on algorithms from the BioNet package (Beisser et al., Bioinformatics 2010). A pipeline is also specifically designed for cellHTS2 object to perform integrative network analyses of high-throughput RNA interference screens. The users can build their own analysis pipeline for their own data set based on this package.

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Version

Version

2.20.0

License

Artistic-2.0

Maintainer

Xin Wang

Last Published

February 15th, 2017

Functions in HTSanalyzeR (2.20.0)

analyzeGeneSetCollections

Hypergeometric tests and Gene Set Enrichment Analyses over a list of gene set collections

writeHTSAHtmlTab

Write tabs to report htmls

writeHTSAHtmlTable

Write a table to report htmls

Aggregate p-values from gene set over-representation tests.

Gene Set Collection Analysis or NetWork Analysis

Select top significant gene sets from GSEA results

permutationPvalueCollectionGsea

Compute the GSEA p-values for a list of gene sets

Check parameters

Plot and save a figure of the enriched subnetwork

A preprocessing method for objects of class GSCA or NWA

annotationConvertor

Convert between different types of gene identifiers

GenHTSAHtmlRowUnit

Generate html codes for one unit of a row of a table

Append gene set terms to GSCA results

biogridDataDownload

Download and extract a network interaction matrix from a BioGRID data set

Plot GSEA results for one gene set

Compute enrichment scores for GSEA (Gene Set Enrichment Analysis)

makeOverlapTable

Find and save the overlapped genes between a gene set and a vector of hits

Produce GSEA plots

networkAnalysis

Identify enriched subnetworks

Plot the enriched subnetwork

Plot a figure of the enriched subnetwork

Plot a figure of GSEA results for one gene set

htmlAttrVectorPaste

Collapse an attribute vector for a table unit

pairwiseGseaPlot

Produce a plot for pairwise GSEA result on one gene set

HTSanalyzeR-package

HTSanalyzeR Package Overview

pairwisePhenoMannWhit

Mann-Whitney U test for shift in location of genes from gene sets on a pair of phenotypes

writeHTSAHtmlTail

Write the tail part of report htmls

writeReportHTSA

Write HTML reports for enrichment and/or network analyses

cellHTS2OutputStatTests

Perform statistical tests on a cellHTS object

celAnnotationConvertor

Convert between different types of gene identifiers for Caenorhabditis Elegans

duplicateRemover

Remove duplicates in a named vector of phenotypes

mammalAnnotationConvertor

Convert between different types of identifiers for mammalian species

FDRcollectionGsea

Compute the GSEA false discovery rates for a collection (list) of gene sets

multiHyperGeoTest

Hypergeometric tests on a list of gene sets

Print summary information for an object of class GSCA or NWA

Plot a figure of the enrichment map for GSEA or Hypergeometric tests

A Sample data set of the package HTSanalyzeR

drosoAnnotationConvertor

Convert between different types of gene identifiers for Drosophila Melanogaster

Performs hypergeometric tests for over-representation analysis

HTSanalyzeR4cellHTS2

An analysis pipeline for cellHTS2 objects

An S4 class for NetWork Analysis on high-throughput screens

GSEA on a pair of phenotypes

writeHTSAHtmlHead

Write the head part of report htmls

writeHTSAHtmlSummary

Write the summary part of report htmls

View new changes made in the latest version

Create a list of gene sets based on GO terms

Compute observed and permutation-based enrichment scores for a collection (list) of gene sets

An S4 class for Gene Set Collection Analyses on high-throughput screens

Create an interactome from BioGRID data sets

Create a list of gene sets based on KEGG pathways terms

Plot and save an enrichment map for results of GSEA or hypergeometric tests

Plot and save figures of GSEA results for top significant gene sets

Write HTML reports for enrichment or network analyses

Write HTML reports for both the enrichment and network analyses