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- W4308132330 abstract "Extracting dynamical information from single-cell transcriptomics is a novel task with the promise to advance our understanding of cell state transition and interactions between genes. Yet, theory-oriented, bottom-up approaches that consider differences among cell states are largely lacking. Here, we present spliceJAC, a method to quantify the multivariate mRNA splicing from single-cell RNA sequencing (scRNA-seq). spliceJAC utilizes the unspliced and spliced mRNA count matrices to constructs cell state-specific gene-gene regulatory interactions and applies stability analysis to predict putative driver genes critical to the transitions between cell states. By applying spliceJAC to biological systems including pancreas endothelium development and epithelial-mesenchymal transition (EMT) in A549 lung cancer cells, we predict genes that serve specific signaling roles in different cell states, recover important differentially expressed genes in agreement with pre-existing analysis, and predict new transition genes that are either exclusive or shared between different cell state transitions." @default.
- W4308132330 created "2022-11-08" @default.
- W4308132330 creator A5015146606 @default.
- W4308132330 creator A5072894189 @default.
- W4308132330 creator A5076311980 @default.
- W4308132330 date "2022-11-01" @default.
- W4308132330 modified "2023-10-14" @default.
- W4308132330 title "<scp>spliceJAC</scp> : transition genes and state‐specific gene regulation from single‐cell transcriptome data" @default.
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- W4308132330 doi "https://doi.org/10.15252/msb.202211176" @default.
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