Computational and Chemical Biology, Fondazione Istituto Italiano di Tecnologia, Genoa 16163, Italy.
Department of Pharmacy and Biotechnology, University of Bologna, Bologna 40126, Italy.
Bioinformatics. 2020 Nov 1;36(17):4664-4667. doi: 10.1093/bioinformatics/btaa273.
A primary problem in high-throughput genomics experiments is finding the most important genes involved in biological processes (e.g. tumor progression). In this applications note, we introduce spathial, an R package for navigating high-dimensional data spaces. spathial implements the Principal Path algorithm, which is a topological method for locally navigating on the data manifold. The package, together with the core algorithm, provides several high-level functions for interpreting the results. One of the analyses we propose is the extraction of the genes that are mainly involved in the progress from one state to another. We show a possible application in the context of tumor progression using RNA-Seq and single-cell datasets, and we compare our results with two commonly used algorithms, edgeR and monocle3, respectively.
The R package spathial is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/spathial/index.html) and on GitHub (https://github.com/erikagardini/spathial). It is distributed under the GNU General Public License (version 3).
Supplementary data are available at Bioinformatics online.
高通量基因组学实验中的一个主要问题是找到参与生物过程(例如肿瘤进展)的最重要基因。在本应用说明中,我们介绍了 spathial,这是一个用于导航高维数据空间的 R 包。spathial 实现了主路径算法,这是一种在数据流形上局部导航的拓扑方法。该软件包与核心算法一起提供了几个用于解释结果的高级功能。我们提出的分析之一是提取主要参与从一种状态到另一种状态进展的基因。我们使用 RNA-Seq 和单细胞数据集展示了在肿瘤进展方面的一个可能应用,并将我们的结果与两个常用算法 edgeR 和 monocle3 进行了比较。
spathial R 包可在 Comprehensive R Archive Network(https://cran.r-project.org/web/packages/spathial/index.html)和 GitHub(https://github.com/erikagardini/spathial)上获得。它根据 GNU 通用公共许可证(第 3 版)分发。
补充数据可在 Bioinformatics 在线获得。