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HTSanalyzeR: an R/Bioconductor package for integrated network analysis of high-throughput screens
Motivation: High-throughput screens (HTS) by RNAi or small molecules are among the most promising tools in functional genomics. They enable researchers to observe detailed reactions to experimental perturbations on a genome-wide scale. While there is a core set of computational approaches used in ma...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3051329/ https://www.ncbi.nlm.nih.gov/pubmed/21258062 http://dx.doi.org/10.1093/bioinformatics/btr028 |
Sumario: | Motivation: High-throughput screens (HTS) by RNAi or small molecules are among the most promising tools in functional genomics. They enable researchers to observe detailed reactions to experimental perturbations on a genome-wide scale. While there is a core set of computational approaches used in many publications to analyze these data, a specialized software combining them and making them easily accessible has so far been missing. Results: Here we describe HTSanalyzeR, a flexible software to build integrated analysis pipelines for HTS data that contains over-representation analysis, gene set enrichment analysis, comparative gene set analysis and rich sub-network identification. HTSanalyzeR interfaces with commonly used pre-processing packages for HTS data and presents its results as HTML pages and network plots. Availability: Our software is written in the R language and freely available via the Bioconductor project at http://www.bioconductor.org. Contact: florian.markowetz@cancer.org.uk |
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