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  "Title": "Cell Type Deconvolution of Spatial Transcriptomics with Dampened\nWeighted Least Squares",
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  "Authors@R": "c(\nperson(\"Rui\", \"Dong\", role = \"aut\",\ncomment = \"original spatialDWLS method and implementation\"),\nperson(\"Guo-Cheng\", \"Yuan\", email = \"guo-cheng.yuan@mssm.edu\",\nrole = \"aut\"),\nperson(\"Ruben\", \"Dries\", email = \"rubendries@gmail.com\",\nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0001-7650-7754\")),\nperson(\"Jiaji\", \"George Chen\", email = \"jiajic@bu.edu\", role = \"ctb\",\ncomment = \"package and website\")\n)",
  "Description": "Estimates the cell type composition of each spot of a\nspatial transcriptomics experiment from a single-cell\nreference, following spatialDWLS (Dong and Yuan 2021,\n<doi:10.1186/s13059-021-02362-7>), which builds on dampened\nweighted least squares (DWLS; Tsoucas et al. 2019,\n<doi:10.1038/s41467-019-10802-z>). Spots are solved in two\nrounds: candidate cell types are chosen per cluster by\nenrichment, then each spot is re-solved against the types\npresent in it. Works on dense or sparse matrices, in parallel\nthrough 'BiocParallel', and over windows of spots for\nexpression stores that do not fit in memory.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "URL": "https://drieslab.github.io/spatialDWLS/,\nhttps://github.com/drieslab/spatialDWLS",
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  "Date/Publication": "2026-10-16 14:36:46 UTC",
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  "_created": "2026-10-16T17:42:34.000Z",
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    "message": "Author order: original method authors first\n\nRui Dong and Guo-Cheng Yuan, who wrote spatialDWLS, are listed first;\nRuben Dries stays maintainer; George Chen is a contributor for the\npackage and website. The Giotto article's render script no longer\nneeds a local Giotto checkout now that Giotto 4.3.2 is merged; its\noutputs re-rendered byte-identical against the merged Giotto.\n\nCo-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>\n",
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