Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.04.369108v1?rss=1 Authors: Chang, Y., Allen, C., Wan, C., Chung, D., Zhang, C., Li, Z., Ma, Q. Abstract: 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. Copy rights belong to original authors. Visit the link for more info