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  "Title": "Interpretation of Heterogeneous Single-Cell Gene Expression Data",
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  "Authors@R": "c(person(given = \"Kun\", family = \"Qian\", role = c(\"aut\",\"ctb\",\"cre\"), email = \"Kun_Qian@foxmail.com\", comment = c(ORCID = \"0000-0002-2354-2238\")),\nperson(given = \"Wei Vivian\", family = \"Li\", role = c(\"aut\",\"ctb\"), email = \"vivian.li@rutgers.edu\", comment = c(ORCID = \"0000-0002-2087-2709\")))",
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  "Description": "We develop a novel matrix factorization tool named\n'scINSIGHT' to jointly analyze multiple single-cell gene\nexpression samples from biologically heterogeneous sources,\nsuch as different disease phases, treatment groups, or\ndevelopmental stages. Given multiple gene expression samples\nfrom different biological conditions, 'scINSIGHT'\nsimultaneously identifies common and condition-specific gene\nmodules and quantify their expression levels in each sample in\na lower-dimensional space. With the factorized results, the\ninferred expression levels and memberships of common gene\nmodules can be used to cluster cells and detect cell\nidentities, and the condition-specific gene modules can help\ncompare functional differences in transcriptomes from distinct\nconditions. Please also see Qian K, Fu SW, Li HW, Li WV (2022)\n<doi:10.1186/s13059-022-02649-3>.",
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