Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq
By Dylan Kotliar, A. Veres, M. Nagy, S. Tabrizi, Eran Hodis, D. Melton, Pardis C Sabeti. bioRxiv, 2018
442 citations recorded by the source corpus.
Identifying gene expression programs underlying both cell-type identity and cellular activities (e.g. life-cycle processes, responses to environmental cues) is crucial for understanding the organization of cells and tissues. Although single-cell RNA-Seq (scRNA-Seq) can quantify transcripts in individual cells, each cell’s expression profile may be a mixture of both types of programs, making them difficult to disentangle. Here we illustrate and enhance the use of matrix factorization as a solution to this problem. We show with simulations that a method that we call consensus non-negative matrix factorization (cNMF) accurately infers identity and activity programs, including the relative contribution of programs in each cell. Applied to published brain organoid and visual cortex scRNA-Seq datasets, cNMF refines the hierarchy of cell types and identifies both expected (e.g. cell cycle and hypoxia) and intriguing novel activity programs. We propose that one of the novel programs may reflect a neurosecretory phenotype and a second may underlie the formation of neuronal synapses. We make cNMF available to the community and illustrate how this approach can provide key insights into gene expression variation within and between cell types.
Subfields: Molecular Biology, Neurology
View Paper: https://www.semanticscholar.org/paper/c36dc095292d6d03e3b5c0889f8bc7c652364af6
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Citations in the corpus
- Cell2location maps fine-grained cell types in spatial transcriptomics (2022, methodology): “Similarly to the established benefits of applying NMF to conventional scRNA-seq 38,39 , the additive NMF decomposition yielded a grouping of spatial cell type abundance profiles into components that capture co-localized cell types.”
- Spatially organized multicellular immune hubs in human colorectal cancer (2021, background): “However, these studies focused on discrete cell clusters and did not capture the full spectrum of transcriptional programs, which can exist as continuous gradients of program activities within or across clusters (Bielecki et al., 2021; Kotliar et al., 2019).”