Faux Thomas, Rytkönen Kalle T, Laiho Asta, Elo Laura L
Turku Bioscience Centre, University of Turku and Åbo Akademi University, Tykistökatu 6, 20520, Turku, Finland.
Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Kiinamyllynkatu 10, 20014, Turku, Finland.
BMC Res Notes. 2019 Jul 19;12(1):441. doi: 10.1186/s13104-019-4473-z.
Visualization of sequencing data is an integral part of genomic data analysis. Although there are several tools to visualize sequencing data on genomic regions, they do not offer user-friendly ways to view simultaneously different groups of replicates. To address this need, we developed a tool that allows efficient viewing of both intra- and intergroup variation of sequencing counts on a genomic region, as well as their comparison to the output of user selected analysis methods, such as peak calling.
We present an R package RepViz for replicate-driven visualization of genomic regions. With ChIP-seq and ATAC-seq data we demonstrate its potential to aid visual inspection involved in the evaluation of normalization, outlier behavior, detected features from differential peak calling analysis, and combined analysis of multiple data types. RepViz is readily available on Bioconductor ( https://www.bioconductor.org/packages/devel/bioc/html/RepViz.html ) and on Github ( https://github.com/elolab/RepViz ).
测序数据的可视化是基因组数据分析不可或缺的一部分。虽然有多种工具可用于在基因组区域可视化测序数据，但它们并未提供用户友好的方式来同时查看不同组的重复数据。为满足这一需求，我们开发了一种工具，该工具能够高效查看基因组区域上测序计数的组内和组间变异，以及将它们与用户选择的分析方法（如峰值检测）的输出结果进行比较。
我们展示了一个用于基因组区域重复驱动可视化的R包RepViz。通过ChIP-seq和ATAC-seq数据，我们证明了它在辅助视觉检查方面的潜力，这些检查涉及归一化评估、异常值行为、差异峰值检测分析中检测到的特征以及多种数据类型的综合分析。RepViz可在Bioconductor（https://www.bioconductor.org/packages/devel/bioc/html/RepViz.html）和Github（https://github.com/elolab/RepViz）上获取。
