PeakMatcher: Matching Peaks Across Genome Assemblies
PeakMatcher: Matching Peaks Across Genome Assemblies
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PeakMatcher：跨基因组组件匹配峰
DOI：
10.1145/3388440.3414907
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Duman-Scheel, Molly
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文献类型：
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作者：
Nowling, Ronald J.;Beal, Christopher R.;Emrich, Scott;Behura, Susanta K.;Halfon, Marc S.;Duman-Scheel, Molly
当更新参考基因组组装时，需要使用新的基因组组装再次调用来自DNA富集测定（例如ChIP-Seq和FAIRE-Seq）的峰。PeakMatcher是一个开源软件包，通过使用读取比对或在同一基因组内匹配两个基因组组装体的峰来辅助验证。PeakMatcher计算召回率和精确度，同时还输出峰到峰匹配列表。PeakMatcher使用读取比对来匹配基因组组装中的峰。PeakMatcher找到与给定的峰列表重叠的与一个基因组对齐的所有读段。PeakMatcher使用读段名称来定位那些读段与第二基因组比对的位置。最后，找到并输出针对第二基因组调用的与比对的读段重叠的所有峰。PeakMatcher组使用峰-读-峰关系来发现1对1、1对多和多对多关系。重叠查询使用区间树来执行，以获得最大的效率。我们在两个数据集上评估了PeakMatcher。第一个数据集是埃及伊蚊胚胎DNA分离的FAIRE-Seq（甲醛辅助分离调控元件测序）[2，4]。我们实现了一个峰值调用管道，并在旧的（高度碎片化的）AaegL 3程序集上验证了它[5]。PeakMatcher匹配了来自[2，4]的121，594个先前调用的峰值中的92.9%（精确度）与我们新管道调用的124，959个峰值中的89.4%（召回率）。接下来，我们应用峰调用流水线来调用FAIRE峰，使用较新的染色体完整的AaegL 5组装[3]。PeakMatcher发现了来自[2，4]的16个实验验证的AaegL 3 FAIRE峰中的14个。我们通过比较基因组中邻近的基因来验证匹配。14个峰中有11个峰的附近基因是一致的;其余峰中至少有两个峰的不一致明显归因于组装的差异。当应用于所有峰时，峰匹配器匹配124，959个AaegL 3峰中的78.8%（精确度）与128，307个AaegL 5峰中的76.7%（召回率）。第二个数据集是S2培养细胞中黑腹果蝇DNA的STARR-Seq（自转录活性调控区测序）[1]。我们对两个版本（dm 3和r5.53）的D.黑腹果蝇基因组[6]。PeakMatcher匹配了4，195 dm 3峰值中的77.4%（精确度）和3，114 r5.53峰值中的94.8%（召回率）。PeakMatcher和相关文档可以在开源Apache软件许可证v2下的GitHub（https：//github.com/rnowling/peak-matcher）上获得。PeakMatcher是用Python 3使用intervaltree库编写的。
When reference genome assemblies are updated, the peaks from DNA enrichment assays such as ChIP-Seq and FAIRE-Seq need to be called again using the new genome assembly. PeakMatcher is an open-source package that aids in validation by matching peaks across two genome assemblies using the alignment of reads or within the same genome. PeakMatcher calculates recall and precision while also outputting lists of peak-to-peak matches.PeakMatcher uses read alignments to match peaks across genome assemblies. PeakMatcher finds all read aligned to one genome that overlap with a given list of peaks. PeakMatcher uses the read names to locate where those reads are aligned against a second genome. Lastly, all peaks called against the second genome that overlap with the aligned reads are found and output. PeakMatcher groups uses the peak-read-peak relationships to discover 1-to-1, 1-to-many, and many-to-many relationships. Overlap queries are performed with interval trees for maximum efficiency.We evaluated PeakMatcher on two data sets. The first data set was FAIRE-Seq (Formaldehyde-Assisted Isolation of Regulatory Elements Sequencing) of DNA isolated embyros of the mosquito Aedes aegypti [2, 4]. We implemented a peak calling pipeline and validated it on the older (highly fragmented) AaegL3 assembly [5]. PeakMatcher matched 92.9% (precision) of the 121,594 previously-called peaks from [2, 4] with 89.4% (recall) of the 124,959 peaks called with our new pipeline. Next, we applied the peak-calling pipeline to call FAIRE peaks using the newer, chromosome-complete AaegL5 assembly [3]. PeakMatcher found matches for 14 of the 16 experimentally-validated AaegL3 FAIRE peaks from [2, 4]. We validated the matches by comparing nearby genes across the genomes. Nearby genes were consistent for 11 of the 14 peaks; inconsistencies for at least two of the remaining peaks were clearly attributable to differences in assemblies. When applied to all of the peaks, Peak-Matcher matched 78.8% (precision) of the 124,959 AaegL3 peaks with 76.7% (recall) of the 128,307 AaegL5 peaks.The second data set was STARR-Seq (Self-Transcribing Active Regulatory Region Sequencing) of Drosophila melanogaster DNA in S2 culture cells [1]. We called STARR peaks against two versions (dm3 and r5.53) of the D. melanogaster genome [6]. PeakMatcher matched 77.4% (precision) of the 4,195 dm3 peaks with 94.8% (recall) of the 3,114 r5.53 peaks.PeakMatcher and associated documentation are available on GitHub (https://github.com/rnowling/peak-matcher) under the open-source Apache Software License v2. PeakMatcher was written in Python 3 using the intervaltree library.