PIPETS: A statistically robust, gene-annotation agnostic analysis method to study bacterial termination using 3'-end sequencing.
PIPETS: A statistically robust, gene-annotation agnostic analysis method to study bacterial termination using 3'-end sequencing.
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PIPETS：一种统计稳健、基因注释不可知的分析方法，用于使用 3 端测序研究细菌终止。
DOI：
10.1101/2024.03.18.585559
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发表时间：
2024
期刊：
影响因子：
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通讯作者：
Meyer,Michelle
中科院分区：
文献类型：
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作者：
Furumo,Quinlan;Meyer,Michelle
背景在过去的十年中，短读测序成本的下降使得利用测序来解决特定生物学问题的实验技术得以激增，通常超过了所产生数据的标准化或有效分析方法。有越来越多的细菌3′端测序数据，但目前还没有普遍接受的分析方法，这种数据类型。大多数数据分析方法都有些复杂，尽管注释基因中存在大量信号，但主要集中在注释基因之外的基因组区域（例如3′或5′ UTR）。此外，缺乏一致的系统分析方法，以及缺乏全基因组的地面真相数据，使它不可能比较不同的实验室产生的结论，使用不同的organis.ResultsWe目前PIPETS，（泊松识别的PEaks从术语-Seq数据），一个R包Bioconductor提供了一种新的分析方法为3 '端测序数据。PIPETS是一种统计信息，基因注释不可知的方法。在来自两种不同生物体的两个不同数据集中，PIPETS在比现有分析方法更宽范围的注释基因组背景中鉴定了显著的3 '末端终止信号，这表明现有方法可能错过生物学相关信号。此外，以前所谓的3′-端位置未捕获的PIPETS评估表明，他们是一致的非常低的coverage.ConclusionsPIPETS提供了一个广泛适用的平台，探索和分析3′-端测序数据集，从不同的生物体。它只需要3′-末端测序数据，并且非专家用户可以广泛访问。
BackgroundOver the last decade the drop in short-read sequencing costs has allowed experimental techniques utilizing sequencing to address specific biological questions to proliferate, oftentimes outpacing standardized or effective analysis approaches for the data generated. There are growing amounts of bacterial 3′-end sequencing data, yet there is currently no commonly accepted analysis methodology for this datatype. Most data analysis approaches are somewhatad hocand, despite the presence of substantial signal within annotated genes, focus on genomic regions outside the annotated genes (e.g. 3′ or 5′ UTRs). Furthermore, the lack of consistent systematic analysis approaches, as well as the absence of genome-wide ground truth data, make it impossible to compare conclusions generated by different labs, using different organisms.ResultsWe present PIPETS, (Poisson Identification of PEaks from Term-Seq data), an R package available on Bioconductor that provides a novel analysis method for 3'-end sequencing data. PIPETS is a statistically informed, gene-annotation agnostic methodology. Across two different datasets from two different organisms, PIPETS identified significant 3'-end termination signal across a wider range of annotated genomic contexts than existing analysis approaches, suggesting that existing approaches may miss biologically relevant signal. Furthermore, assessment of the previously called 3′-end positions not captured by PIPETS showed that they were uniformly very low coverage.ConclusionsPIPETS provides a broadly applicable platform to explore and analyze 3′-end sequencing data sets from across different organisms. It requires only the 3′-end sequencing data, and is broadly accessible to non-expert users.