OLOGRAM: determining significance of total overlap length between genomic regions sets
OLOGRAM: determining significance of total overlap length between genomic regions sets
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DOI：
10.1093/bioinformatics/btz810
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发表时间：
2020-03-15
期刊：
影响因子：
5.8
通讯作者：
Puthier, D.
中科院分区：
文献类型：
--
作者：
Ferre, Q.;Charbonnier, G.;Puthier, D.
动机：各种生物信息学分析提供了感兴趣的基因组坐标集。两个这样的集合是否具有函数关系是一个常见的问题。这通常是通过解释其重叠的统计意义来确定的。然而，只有少数现有的方法考虑的重叠的长度，他们不提供一个分辨率的P-value.Results：在这里，我们介绍OLOGRAM，它执行重叠的统计数据集的基因组区域中描述的BEDs或GTF。它使用蒙特卡罗模拟，考虑到区域和区域间长度的分布，以拟合总重叠长度的负二项模型。支持在改组期间排除用户定义的基因组区域。
Motivation: Various bioinformatics analyses provide sets of genomic coordinates of interest. Whether two such sets possess a functional relation is a frequent question. This is often determined by interpreting the statistical significance of their overlaps. However, only few existing methods consider the lengths of the overlap, and they do not provide a resolutive P-value.Results: Here, we introduce OLOGRAM, which performs overlap statistics between sets of genomic regions described in BEDs or GTF. It uses Monte Carlo simulation, taking into account both the distributions of region and inter-region lengths, to fit a negative binomial model of the total overlap length. Exclusion of user-defined genomic areas during the shuffling is supported.