LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor.
LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor.
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DOI：
10.1093/bioinformatics/btv612
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发表时间：
2016-02-15
期刊：
影响因子：
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通讯作者：
Bock C
中科院分区：
文献类型：
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作者：
Sheffield NC;Bock C
摘要：基因组数据集通常是在大规模参考数据库的背景下解释的。一种方法是识别显著重叠的基因集，这对以基因为中心的数据很有效。然而，许多类型的高通量数据都是基于基因组区域的。基因座重叠分析(LOLA)为基因组区域集提供了简单和自动化的富集化分析，从而促进了功能基因组学和表观基因组学数据的解释。可用性和实施：R包可在BioConductor上获得，也可在以下网站上获得：http://lola.computational-epigenetics.org.联系人：nshefffield@cemm.oeaw.ac.at或cbock@cemm.oeaw.ac.at
Summary: Genomic datasets are often interpreted in the context of large-scale reference databases. One approach is to identify significantly overlapping gene sets, which works well for gene-centric data. However, many types of high-throughput data are based on genomic regions. Locus Overlap Analysis (LOLA) provides easy and automatable enrichment analysis for genomic region sets, thus facilitating the interpretation of functional genomics and epigenomics data. Availability and Implementation: R package available in Bioconductor and on the following website: http://lola.computational-epigenetics.org. Contact: nsheffield@cemm.oeaw.ac.at or cbock@cemm.oeaw.ac.at