O'Connell Michael J, Lock Eric F
Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA.
Bioinformatics. 2016 Sep 15;32(18):2877-9. doi: 10.1093/bioinformatics/btw324. Epub 2016 Jun 6.
: The integrative analysis of multiple high-throughput data sources that are available for a common sample set is an increasingly common goal in biomedical research. Joint and individual variation explained (JIVE) is a tool for exploratory dimension reduction that decomposes a multi-source dataset into three terms: a low-rank approximation capturing joint variation across sources, low-rank approximations for structured variation individual to each source and residual noise. JIVE has been used to explore multi-source data for a variety of application areas but its accessibility was previously limited. We introduce R.JIVE, an intuitive R package to perform JIVE and visualize the results. We discuss several improvements and extensions of the JIVE methodology that are included. We illustrate the package with an application to multi-source breast tumor data from The Cancer Genome Atlas.
R.JIVE is available via the Comprehensive R Archive Network (CRAN) under the GPLv3 license: https://cran.r-project.org/web/packages/r.jive/
Supplementary data are available at Bioinformatics online.
对可用于同一样本集的多个高通量数据源进行综合分析是生物医学研究中日益常见的目标。联合和个体变异解释（JIVE）是一种用于探索性降维的工具，它将多源数据集分解为三个部分：一个捕获各源间联合变异的低秩近似、每个源特有的结构化变异的低秩近似以及残余噪声。JIVE已被用于探索多个应用领域的多源数据，但其易用性此前受到限制。我们引入了R.JIVE，一个用于执行JIVE并可视化结果的直观R包。我们讨论了所包含的JIVE方法的若干改进和扩展。我们通过应用于来自癌症基因组图谱的多源乳腺肿瘤数据来说明该包。
R.JIVE可通过综合R存档网络（CRAN）以GPLv3许可获取：https://cran.r-project.org/web/packages/r.jive/
补充数据可在《生物信息学》在线获取。
