{ "_id": "6a1b01071d7bb097a09ffe11", "Package": "MOFA2", "Type": "Package", "Title": "Multi-Omics Factor Analysis v2", "Version": "1.23.0", "Maintainer": "Ricard Argelaguet ", "Authors@R": "c(person(\"Ricard\", \"Argelaguet\", role = c(\"aut\", \"cre\"),\nemail = \"ricard.argelaguet@gmail.com\",\ncomment = c(ORCID = \"http://orcid.org/0000-0003-3199-3722\")),\nperson(\"Damien\", \"Arnol\", role = \"aut\",\nemail = \"damien.arnol@gmail.com\",\ncomment = c(ORCID = \"http://orcid.org/0000-0003-2462-534X\")),\nperson(\"Danila\", \"Bredikhin\", role = \"aut\",\nemail = \"danila.bredikhin@embl.de\",\ncomment = c(ORCID = \"https://orcid.org/0000-0001-8089-6983\")),\nperson(\"Britta\", \"Velten\", role = \"aut\",\nemail = \"britta.velten@gmail.com\",\ncomment = c(ORCID = \"http://orcid.org/0000-0002-8397-3515\"))\n)", "Date": "2023-01-12", "License": "file LICENSE", "Description": "The MOFA2 package contains a collection of tools for\ntraining and analysing multi-omic factor analysis (MOFA). MOFA\nis a probabilistic factor model that aims to identify principal\naxes of variation from data sets that can comprise multiple\nomic layers and/or groups of samples. Additional time or space\ninformation on the samples can be incorporated using the\nMEFISTO framework, which is part of MOFA2. 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