Abstract
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 functional gene modules (FGM) can help to understand gene interactive networks and complex biological processes. QUBIC2 is recognized as one of the most efficient and effective tools for FGM identification from scRNA-Seq data. However, its limited availability to a C implementation restricted its application to only a few downstream analyses 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 co-expressed and co-regulated FGMs, predict cell types/clusters, uncover differentially expressed genes, and perform functional enrichment analysis. It is noteworthy that IRIS-FGM can also takes Seurat objects as input, which facilitate easy integration with existing analysis pipeline.
Availability and Implementation IRIS-FGM is implemented in R environment (as of version 3.6) with the source code freely available at https://github.com/OSU-BMBL/IRIS-FGM
Contact qin.ma{at}osumc.edu
Supplementary information Supplementary data are available at Bioinformatics online.
Competing Interest Statement
The authors have declared no competing interest.