IRIS-FGM：用于功能基因模块分析的综合单细胞 RNA-Seq 解读系统。
IRIS-FGM: an integrative single-cell RNA-Seq interpretation system for functional gene module analysis.
机构信息
Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.
Center for Computational Biology and Bioinformatics and Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
出版信息
Bioinformatics. 2021 Sep 29;37(18):3045-3047. doi: 10.1093/bioinformatics/btab108.
SUMMARY
Single-cell RNA-Seq (scRNA-Seq) data is useful in discovering cell heterogeneity and signature genes in specific cell populations in cancer and other complex diseases. Specifically, the investigation of condition-specific functional gene modules (FGM) can help to understand interactive gene networks and complex biological processes in different cell clusters. QUBIC2 is recognized as one of the most efficient and effective biclustering tools for condition-specific FGM identification from scRNA-Seq data. However, its limited availability to a C implementation restricted its application to only a few downstream analysis functionalities. We developed an R package named IRIS-FGM (Integrative scRNA-Seq Interpretation System for Functional Gene Module analysis) to support the investigation of FGMs and cell clustering using scRNA-Seq data. Empowered by QUBIC2, IRIS-FGM can effectively identify condition-specific FGMs, predict cell types/clusters, uncover differentially expressed genes and perform pathway enrichment analysis. It is noteworthy that IRIS-FGM can also take Seurat objects as input, facilitating easy integration with the existing analysis pipeline.
AVAILABILITY AND IMPLEMENTATION
IRIS-FGM is implemented in the R environment (as of version 3.6) with the source code freely available at https://github.com/BMEngineeR/IRISFGM.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
单细胞 RNA 测序（scRNA-Seq）数据可用于发现癌症和其他复杂疾病中特定细胞群体的细胞异质性和特征基因。具体来说，研究特定条件下的功能基因模块（FGM）有助于理解不同细胞簇中相互作用的基因网络和复杂的生物学过程。QUBIC2 被认为是从 scRNA-Seq 数据中识别特定条件下 FGM 的最有效和最有效的双聚类工具之一。然而，由于其 C 实现的有限可用性，限制了其仅应用于少数下游分析功能。我们开发了一个名为 IRIS-FGM（用于功能基因模块分析的集成 scRNA-Seq 解释系统）的 R 包，用于支持使用 scRNA-Seq 数据研究 FGM 和细胞聚类。在 QUBIC2 的支持下，IRIS-FGM 可以有效地识别特定条件下的 FGM，预测细胞类型/簇，发现差异表达基因，并进行途径富集分析。值得注意的是，IRIS-FGM 还可以接受 Seurat 对象作为输入，便于与现有的分析流程轻松集成。
可用性和实现
IRIS-FGM 是在 R 环境中实现的（截至版本 3.6），源代码可在 https://github.com/BMEngineeR/IRISFGM 上免费获得。
补充信息
补充数据可在生物信息学在线获得。
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