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Decoding the building blocks of cellular processes from single-cell transcriptomics data
Most features of a cell are determined by gene programs — sets of co-expressed genes that execute a specific function. By incorporating existing knowledge about gene programs and cell types, the Spectra factor analysis method improves how we decode single-cell transcriptomic data and offers insights into challenging tumor immune contexts.
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Detection of transcriptome-wide microRNA–target interactions in single cells with agoTRIBE
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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes
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Supervised discovery of interpretable gene programs from single-cell data
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Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens