SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data.

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Journal of Statistical Software Pub Date : 2021-07-01 Epub Date: 2021-07-10 DOI:10.18637/jss.v098.i12
Tyler Grimes, Somnath Datta
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引用次数: 0

Abstract

Gene expression data provide an abundant resource for inferring connections in gene regulatory networks. While methodologies developed for this task have shown success, a challenge remains in comparing the performance among methods. Gold-standard datasets are scarce and limited in use. And while tools for simulating expression data are available, they are not designed to resemble the data obtained from RNA-seq experiments. SeqNet is an R package that provides tools for generating a rich variety of gene network structures and simulating RNA-seq data from them. This produces in silico RNA-seq data for benchmarking and assessing gene network inference methods. The package is available on CRAN and on GitHub at https://github.com/tgrimes/SeqNet.

Abstract Image

Abstract Image

SeqNet:用于生成基因-基因网络和模拟 RNA-Seq 数据的 R 软件包。
基因表达数据为推断基因调控网络的连接提供了丰富的资源。虽然为这项任务开发的方法已经取得了成功,但在比较各种方法的性能方面仍然存在挑战。黄金标准数据集非常稀缺,而且使用有限。虽然有模拟表达数据的工具,但它们的设计并不类似于从 RNA-seq 实验中获得的数据。SeqNet 是一个 R 软件包,提供了生成各种丰富的基因网络结构并从中模拟 RNA-seq 数据的工具。它生成的硅 RNA-seq 数据可用于基准测试和评估基因网络推断方法。该软件包可在 CRAN 和 GitHub 上获取:https://github.com/tgrimes/SeqNet。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Statistical Software
Journal of Statistical Software 工程技术-计算机:跨学科应用
CiteScore
10.70
自引率
1.70%
发文量
40
审稿时长
6-12 weeks
期刊介绍: The Journal of Statistical Software (JSS) publishes open-source software and corresponding reproducible articles discussing all aspects of the design, implementation, documentation, application, evaluation, comparison, maintainance and distribution of software dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research. Open-source code and articles are jointly reviewed and published in this journal and should be accessible to a broad community of practitioners, teachers, and researchers in the field of statistics.
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