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  "Title": "Analysis of Biological Count Data, Especially from Single-Cell\nRNA-Seq",
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  "Authors@R": "person(\"Church\", \"Samuel H.\", , \"samuelhchurch@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-8451-103X\"))",
  "Description": "A set of functions for applying a restricted linear\nalgebra to the analysis of count-based data. See the\naccompanying preprint manuscript: \"Normalizing need not be the\nnorm: count-based math for analyzing single-cell data\" Church\net al (2022) <doi:10.1101/2022.06.01.494334> This tool is\nspecifically designed to analyze count matrices from single\ncell RNA sequencing assays. The tools implement several\ncount-based approaches for standard steps in single-cell\nRNA-seq analysis, including scoring genes and cells, comparing\ncells and clustering, calculating differential gene expression,\nand several methods for rank reduction. There are many\nopportunities for further optimization that may prove useful in\nthe analysis of other data. We provide the source code freely\navailable at <https://github.com/shchurch/countland> and\nencourage users and developers to fork the code for their own\npurposes.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "URL": "https://github.com/shchurch/countland",
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  "Maintainer": "Church Samuel H. <samuelhchurch@gmail.com>",
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