HTSanalyzeR2: HTSanalyzeR2 Package Overview

Description Details References

Description

This package provides classes and methods for gene set over-representation, enrichment and network analyses on various high-throughput data generated from RNAi, microarray, RNA-seq and CRISPR. 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 unique point of this package compared to other similar packages lies in that it can deal with "Time series" data with high efficiency. In addition, it can generate a dynamic Shiny report including all the results in, which would be easily for users to download, modify visualizations and even share with others. A pipeline is also specifically designed for CRISPR data pre-processed by MAGeCK to perform integrative analyses including gene set over-representation, enrichment and network analyses. The users can also build their own analysis pipeline for their data based on this package.

Details

The most important classes in this package are 'GSCA' (Gene Set Collection Analyses), 'NWA' (NetWork Analyses), 'GSCABatch' (Gene Set Collection Analyses for time-series data) and 'NWABatch' (NetWork Analyses for time-series data). As an example, a pipeline (see function 'HTSanalyzeR4MAGeCK') is developed in this package for CRISPR data preprocessed by MAGeCK. Based on these four classes and other functions, users can design their own pipelines specifically for their own data sets.

Full help on classes and associated functions is available from within class help pages.

Introductory information on the use of classes and pipeline are available in the vignette.

A full listing of documented topics is available in HTML view by typing help.start() and selecting the HTSanalyzeR package from the Packages menu or via library(help="HTSanalyzeR2").

References

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S. & Mesirov, J. P. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545-15550.

Beisser D, Klau GW, Dandekar T, Muller T, Dittrich MT. BioNet: an R-Package for the functional analysis of biological networks. Bioinformatics. 2010 Apr 15;26(8):1129-30.

Dittrich MT, Klau GW, Rosenwald A., Dandekar T and Muller T. Identifying functional modules in protein-protein interaction networks: an integrated exact approach. Bioinformatics 2008 24(13):i223-i231.


CityUHK-CompBio/HTSanalyzeR2 documentation built on Dec. 3, 2020, 2:35 a.m.