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首页> 外文期刊>International journal of computational biology and drug design >NGSPERL: a semi-automated framework for large scale next generation sequencing data analysis
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NGSPERL: a semi-automated framework for large scale next generation sequencing data analysis

机译：NGSPERL：用于大规模下一代测序数据分析的半自动化框架

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摘要

High-throughput sequencing technologies have been widely used in medical and biological research, especially in cancer biology. With the huge amounts of sequencing data being generated, data analysis has become the bottle-neck of the research procedure. We have designed and implemented NGSPERL, a semi-automated module-based framework, for high-throughput sequencing data analysis. Three major analysis pipelines with multiple tasks have been developed for RNA sequencing, exome sequencing, and small RNA sequencing data. Each task was developed as module. The module uses the output from the previous task as the input parameter to generate the corresponding portable batch system (PBS) script. The PBS scripts can be either submitted to cluster or run directly based on user choice. Multiple tasks can also be combined together as a single task to simplify the data analysis. Such a flexible framework will significantly automate and simplify the process of large scale sequencing data analysis.
机译：高通量测序技术已广泛用于医学和生物学研究，尤其是癌症生物学。随着大量测序数据的产生，数据分析已成为研究程序的瓶颈。我们已经设计并实现了NGSPERL，这是一个基于模块的半自动化框架，用于高通量测序数据分析。针对RNA测序，外显子组测序和小RNA测序数据，已经开发出具有三个任务的三个主要分析管道。每个任务都作为模块开发。该模块使用前一个任务的输出作为输入参数来生成相应的便携式批处理系统（PBS）脚本。可以将PBS脚本提交到群集，也可以根据用户选择直接运行。多个任务也可以组合为一个任务，以简化数据分析。这种灵活的框架将极大地自动化和简化大规模测序数据分析的过程。

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