Immunology and Functional Genomics Unit, Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy.
Bioinformatics. 2018 Apr 15;34(8):1416-1418. doi: 10.1093/bioinformatics/btx795.
RNA-Seq is becoming the technique of choice for high-throughput transcriptome profiling, which, besides class comparison for differential expression, promises to be an effective and powerful tool for biomarker discovery. However, a systematic analysis of high-dimensional genomic data is a demanding task for such a purpose. DaMiRseq offers an organized, flexible and convenient framework to remove noise and bias, select the most informative features and perform accurate classification.
DaMiRseq is developed for the R environment (R ≥ 3.4) and is released under GPL (≥2) License. The package runs on Windows, Linux and Macintosh operating systems and is freely available to non-commercial users at the Bioconductor open-source, open-development software project repository (https://bioconductor.org/packages/DaMiRseq/). In compliance with Bioconductor standards, the authors ensure stable package maintenance through software and documentation updates.
Supplementary data are available at Bioinformatics online.
RNA-Seq 正成为高通量转录组分析的首选技术，除了用于差异表达的分类比较外，它有望成为生物标志物发现的有效强大工具。然而，为了达到这个目的，对高维基因组数据进行系统分析是一项具有挑战性的任务。DaMiRseq 为去除噪声和偏差、选择最具信息量的特征以及进行准确分类提供了一个有组织、灵活和方便的框架。
DaMiRseq 是为 R 环境（R ≥ 3.4）开发的，并根据 GPL（≥2）许可证发布。该软件包可在 Windows、Linux 和 Macintosh 操作系统上运行，并且可以在 Bioconductor 开源、开放式开发软件项目存储库（https://bioconductor.org/packages/DaMiRseq/）上免费提供给非商业用户使用。为了符合 Bioconductor 的标准，作者通过软件和文档更新确保了软件包的稳定维护。
补充数据可在 Bioinformatics 在线获得。
