Methods for analyzing next-generation sequencing data 19. R Markdown.-Reference-Cited by-同舟云学术

Methods for analyzing next-generation sequencing data 19. R Markdown.

Published:2022-11-15 Issue:3 Volume:33 Page:195-205
ISSN:1343-327X
Container-title:Japanese Journal of Lactic Acid Bacteria
language:en
Short-container-title:Jpn. J. Lactic Acid Bact.

Author:

Makino Manon¹,Shimizu Kentaro¹,Kadota Koji¹

Affiliation:

1. Graduate School of Agricultural and Life Sciences, The University of Tokyo.

Publisher

Japan Society for Lactic Acid Bacteria

Subject

General Agricultural and Biological Sciences

Link

https://www.jstage.jst.go.jp/article/jslab/33/3/33_195/_pdf

Reference12 articles.

1. 1) Su W, Sun J, Shimizu K, Kadota K (2019) TCC-GUI: a Shiny-based application for differential expression analysis of RNA-Seq count data. BMC Res Notes 12: 133

2. 2) Osabe T, Shimizu K, Kadota K (2021) Differential expression analysis using a model-based gene clustering algorithm for RNA-seq data. BMC Bioinformatics 22: 511.

3. 3) 牧野磨音，清水謙多郎，門田幸二（2022）次世代シーケンサーデータの解析手法：第 18 回遺伝子発現データのクラスタリング，日本乳酸菌学会誌 33: 87-94．

4. 4) Xie Y. (2022) knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.39, https://yihui.org/knitr/.

5. 5) Allaire J, Xie Y, McPherson J, Luraschi J, Ushey K, et al. (2022) rmarkdown: Dynamic Documents for R. R package version 2.14, https://github.com/rstudio/rmarkdown.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Methods for analyzing next-generation sequencing data 20. Properties and statistical models of RNA-seq count data.;Japanese Journal of Lactic Acid Bacteria;2023-03-24