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SeqGSEA:一个用于 RNA-Seq 数据基因集富集分析的 Bioconductor 软件包,集成了差异表达和剪接分析。

SeqGSEA: a Bioconductor package for gene set enrichment analysis of RNA-Seq data integrating differential expression and splicing.

机构信息

School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, AustraliaSchool of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, Australia.

School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, AustraliaSchool of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, AustraliaSchool of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, Hunter Medical Research Institute, New Lambton, and Schizophrenia Research Institute, Sydney, NSW, Australia.

出版信息

Bioinformatics. 2014 Jun 15;30(12):1777-9. doi: 10.1093/bioinformatics/btu090. Epub 2014 Feb 17.

Abstract

SUMMARY

SeqGSEA is an open-source Bioconductor package for the functional integration of differential expression and splicing analysis in RNA-Seq data. SeqGSEA implements an analysis pipeline, which first computes differential splicing and differential expression scores, followed by integrating them into a per-gene score that quantifies each gene's association with a phenotype of interest, and finally executes gene set enrichment analysis in a cutoff-free manner to achieve biological insights. SeqGSEA accounts for biological variability and determines the statistical significance of gene pathways and networks using subject permutation, and thus requires at least five samples per group. Real applications show that SeqGSEA detects more biologically meaningful gene sets without biases toward long or highly expressed genes. SeqGSEA can be set up to run in parallel to reduce the analysis time.

AVAILABILITY AND IMPLEMENTATION

The SeqGSEA package with a vignette is available at http://bioconductor.org/packages/release/bioc/html/SeqGSEA.html.

摘要

摘要

SeqGSEA 是一个用于 RNA-Seq 数据中差异表达和剪接分析功能整合的开源 Bioconductor 包。SeqGSEA 实现了一个分析流程,首先计算差异剪接和差异表达评分,然后将它们整合到每个基因的评分中,该评分量化了每个基因与感兴趣表型的关联程度,最后以无截止方式执行基因集富集分析,以获得生物学见解。SeqGSEA 考虑了生物学变异性,并使用主体置换来确定基因通路和网络的统计显著性,因此每组至少需要五个样本。实际应用表明,SeqGSEA 可以检测到更具生物学意义的基因集,而不会偏向于长或高表达的基因。SeqGSEA 可以设置为并行运行,以减少分析时间。

可用性和实现

带有说明的 SeqGSEA 包可在 http://bioconductor.org/packages/release/bioc/html/SeqGSEA.html 获得。

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