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  "Package": "LRcell",
  "Type": "Package",
  "Title": "Differential cell type change analysis using Logistic/linear\nRegression",
  "Version": "1.21.0",
  "Date": "2021-03-10",
  "Authors@R": "person(\"Wenjing\", \"Ma\", \nemail=\"wenjing.ma@emory.edu\",\nrole=c(\"cre\", \"aut\"),\ncomment = c(ORCID = \"0000-0001-8757-651X\"))",
  "BugReports": "https://github.com/marvinquiet/LRcell/issues",
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  "Description": "The goal of LRcell is to identify specific sub-cell types\nthat drives the changes observed in a bulk RNA-seq differential\ngene expression experiment. To achieve this, LRcell utilizes\nsets of cell marker genes acquired from single-cell\nRNA-sequencing (scRNA-seq) as indicators for various cell types\nin the tissue of interest. Next, for each cell type, using its\nmarker genes as indicators, we apply Logistic Regression on the\ncomplete set of genes with differential expression p-values to\ncalculate a cell-type significance p-value. Finally, these\np-values are compared to predict which one(s) are likely to be\nresponsible for the differential gene expression pattern\nobserved in the bulk RNA-seq experiments. LRcell is inspired by\nthe LRpath[@sartor2009lrpath] algorithm developed by Sartor et\nal., originally designed for pathway/gene set enrichment\nanalysis. LRcell contains three major components: LRcell\nanalysis, plot generation and marker gene selection. All\nmodules in this package are written in R. This package also\nprovides marker genes in the Prefrontal Cortex (pFC) human\nbrain region, human PBMC and nine mouse brain regions (Frontal\nCortex, Cerebellum, Globus Pallidus, Hippocampus,\nEntopeduncular, Posterior Cortex, Striatum, Substantia Nigra\nand Thalamus).",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "biocViews": "SingleCell, GeneSetEnrichment, Sequencing, Regression,\nGeneExpression, DifferentialExpression",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:55:33 UTC",
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