一个可扩展的,灵活的工作流程甲基cap - seq数据分析。

Benjamin Rodriguez, Hok-Hei Tam, David Frankhouser, Michael Trimarchi, Mark Murphy, Chris Kuo, Deval Parikh, Bryan Ball, Sebastian Schwind, John Curfman, William Blum, Guido Marcucci, Pearlly Yan, Ralf Bundschuh
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引用次数: 6

摘要

全基因组图谱的进步使癌症研究领域发生了革命性的变化,但同时也提出了新的生物信息学挑战。对于下一代测序(NGS),这些包括数据存储、计算成本、序列处理和比对、描述适当的统计测量和数据可视化。NGS应用MethylCap-seq包括体外捕获甲基化DNA,随后通过大规模平行测序对富集片段进行分析。在这里,我们提出了一个可扩展的,灵活的工作流程,用于MethylCap-seq质量控制,二级数据分析,多个实验组的三级分析和数据可视化。该工作流程及其功能套件将帮助生物学家进行甲基化分析项目,并促进有意义的生物学解释。
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A Scalable, Flexible Workflow for MethylCap-Seq Data Analysis.

Advances in whole genome profiling have revolutionized the cancer research field, but at the same time have raised new bioinformatics challenges. For next generation sequencing (NGS), these include data storage, computational costs, sequence processing and alignment, delineating appropriate statistical measures, and data visualization. The NGS application MethylCap-seq involves the in vitro capture of methylated DNA and subsequent analysis of enriched fragments by massively parallel sequencing. Here, we present a scalable, flexible workflow for MethylCap-seq Quality Control, secondary data analysis, tertiary analysis of multiple experimental groups, and data visualization. This workflow and its suite of features will assist biologists in conducting methylation profiling projects and facilitate meaningful biological interpretation.

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