Department of Informatics, University of Oslo, Oslo, Norway.
K. G. Jebsen Coeliac Disease Research Centre, Oslo, Norway.
Bioinformatics. 2019 May 1;35(9):1615-1624. doi: 10.1093/bioinformatics/bty835.
Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.
Here, we describe the different approaches and provide recommendations for performing genomic colocalization analysis, while also discussing common methodological challenges that may influence the conclusions. As illustrated by concrete example cases, careful attention to analysis details is needed in order to meet these challenges and to obtain a robust and biologically meaningful interpretation of genomic region set data.
Supplementary data are available at Bioinformatics online.
许多高通量方法将基因组区域集作为其主要输出之一。科学家经常使用基因组共定位分析来解释这些区域集，例如识别有趣的富集，并理解潜在生物学过程之间的相互作用。尽管广泛使用，但这些分析的执行方式几乎没有标准化。不同的实践可以极大地影响共定位分析的结论。
在这里，我们描述了不同的方法，并提供了执行基因组共定位分析的建议，同时还讨论了可能影响结论的常见方法学挑战。通过具体的示例案例说明，需要仔细注意分析细节，以应对这些挑战，并对基因组区域集数据进行稳健且具有生物学意义的解释。
补充数据可在“Bioinformatics”在线获取。
