{ "_id": "6aea27152e87f76f20ad13a7", "Package": "phenoscapR", "Title": "Read, Analyse, and Visualise Single-Cell Spatial Biology Data", "Version": "0.2.0.9001", "Authors@R": "c(\nperson(\"R.\", \"Heller\", email = \"raban.heller@uni-ulm.de\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-8006-9742\",\naffiliation = \"Ulm University\")),\nperson(\"E.\", \"Chteinberg\", role = c(\"aut\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-9231-9291\",\naffiliation = \"Ulm University\")),\nperson(\"H.\", \"Witte\", role = c(\"aut\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-5767-7125\",\naffiliation = \"Ulm University\")))", "Description": "Tools for importing, processing, analysing, and\nvisualising single-cell spatial biology data from multiplexed\nimaging platforms. Supports cell-table quality control, marker\nnormalisation, phenotype summaries, spatial neighbourhood\nstatistics such as Ripley's K function (Ripley (1977)\n) and Moran's I (Moran\n(1950) ), and explicit sample and\ncoordinate-frame registries. Patient-level inference enumerates\nlabel allocations for declared contrasts (exact permutation\ntests; Pitman (1937) ) and retains\nunavailable hypotheses when adjusting for multiple testing.\nGrouped summaries expose missingness, eligibility, and\ndenominator provenance. Optional canonical cell-table import\nuses 'cellspecR' ; optional\nSelf-Organising Nebulous Growths (SONG) embeddings (Senanayake\net al. (2021) ) use 'songR'\n. 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