Genome-wide detection of intervals of genetic heterogeneity associated with complex traits.
Genome-wide detection of intervals of genetic heterogeneity associated with complex traits.
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DOI：
10.1093/bioinformatics/btv263
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发表时间：
2015-06-15
期刊：
影响因子：
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通讯作者：
Borgwardt K
中科院分区：
文献类型：
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作者：
Llinares-López F;Grimm DG;Bodenham DA;Gieraths U;Sugiyama M;Rowan B;Borgwardt K
动机：遗传异质性，即几个序列变体产生相同表型的事实，是复杂表型分析中最感兴趣的现象。目前用于在基因组中发现表现出遗传异质性的区域的方法遭受两个缺点中的至少一个：（i）它们需要在基因组中定义一个精确的区间，该区间将被测试遗传异质性，潜在地缺失高相关性的区间，或者（ii）它们由于大量潜在的候选区间被测试而遭受巨大的多重假设测试问题，这导致许多假阳性或缺乏检测真实间隔的能力。结果如下：在这里，我们提出了一种方法，克服了这两个问题：它允许一个自动找到所有连续序列的单核苷酸多态性的基因组中，共同与表型。它还解决了多假设检验固有的计算效率问题和统计问题，这两个问题都是由大量的候选区间引起的。我们在拟南芥全基因组关联研究数据上证明，我们的方法可以发现表现出遗传异质性的区域，并且会被单位点作图遗漏。结论：我们的新方法有助于在全基因组范围内发现复杂表型的遗传异质性所涉及的间隔。可用性和实施：代码可以在http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/sis.html上获得。联系人：felipe. bsse.ethz.ch补充信息：补充数据可在生物信息学在线获得。
Motivation: Genetic heterogeneity, the fact that several sequence variants give rise to the same phenotype, is a phenomenon that is of the utmost interest in the analysis of complex phenotypes. Current approaches for finding regions in the genome that exhibit genetic heterogeneity suffer from at least one of two shortcomings: (i) they require the definition of an exact interval in the genome that is to be tested for genetic heterogeneity, potentially missing intervals of high relevance, or (ii) they suffer from an enormous multiple hypothesis testing problem due to the large number of potential candidate intervals being tested, which results in either many false positives or a lack of power to detect true intervals. Results: Here, we present an approach that overcomes both problems: it allows one to automatically find all contiguous sequences of single nucleotide polymorphisms in the genome that are jointly associated with the phenotype. It also solves both the inherent computational efficiency problem and the statistical problem of multiple hypothesis testing, which are both caused by the huge number of candidate intervals. We demonstrate on Arabidopsis thaliana genome-wide association study data that our approach can discover regions that exhibit genetic heterogeneity and would be missed by single-locus mapping. Conclusions: Our novel approach can contribute to the genome-wide discovery of intervals that are involved in the genetic heterogeneity underlying complex phenotypes. Availability and implementation: The code can be obtained at: http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/sis.html. Contact: felipe.llinares@bsse.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online.