GLANET：基因组位点注释和富集工具。
GLANET: genomic loci annotation and enrichment tool.
机构信息
Department of Computer Engineering, Middle East Technical University, 06800, Ankara, Turkey.
Department of Computer Engineering, Bilkent University, 06800, Ankara, Turkey.
出版信息
Bioinformatics. 2017 Sep 15;33(18):2818-2828. doi: 10.1093/bioinformatics/btx326.
MOTIVATION
Genomic studies identify genomic loci representing genetic variations, transcription factor (TF) occupancy, or histone modification through next generation sequencing (NGS) technologies. Interpreting these loci requires evaluating them with known genomic and epigenomic annotations.
RESULTS
We present GLANET as a comprehensive annotation and enrichment analysis tool which implements a sampling-based enrichment test that accounts for GC content and/or mappability biases, jointly or separately. GLANET annotates and performs enrichment analysis on these loci with a rich library. We introduce and perform novel data-driven computational experiments for assessing the power and Type-I error of its enrichment procedure which show that GLANET has attained high statistical power and well-controlled Type-I error rate. As a key feature, users can easily extend its library with new gene sets and genomic intervals. Other key features include assessment of impact of single nucleotide variants (SNPs) on TF binding sites and regulation based pathway enrichment analysis.
AVAILABILITY AND IMPLEMENTATION
GLANET can be run using its GUI or on command line. GLANET's source code is available at https://github.com/burcakotlu/GLANET . Tutorials are provided at https://glanet.readthedocs.org .
CONTACT
burcak@ceng.metu.edu.tr or oznur.tastan@cs.bilkent.edu.tr.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
动机
基因组研究通过下一代测序 (NGS) 技术识别代表遗传变异、转录因子 (TF) 占据或组蛋白修饰的基因组位置。解释这些位置需要使用已知的基因组和表观基因组注释来评估它们。
结果
我们提出了 GLANET，它是一种综合注释和富集分析工具，实现了基于抽样的富集测试，可分别或联合考虑 GC 含量和/或可映射性偏差。GLANET 使用丰富的库对这些位置进行注释和富集分析。我们引入并进行了新的基于数据的计算实验，以评估其富集过程的功效和 I 型错误率，结果表明 GLANET 具有较高的统计功效和良好控制的 I 型错误率。作为一个关键功能，用户可以轻松地用新的基因集和基因组间隔来扩展其库。其他关键功能包括评估单核苷酸变异 (SNP) 对 TF 结合位点的影响和基于通路的调控富集分析。
可用性和实现
GLANET 可以使用其 GUI 或命令行运行。GLANET 的源代码可在 https://github.com/burcakotlu/GLANET 上获得。教程可在 https://glanet.readthedocs.org 上找到。
联系人
burcak@ceng.metu.edu.tr 或 oznur.tastan@cs.bilkent.edu.tr。
补充信息
补充数据可在生物信息学在线获得。
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