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  "Package": "IsoBayes",
  "Type": "Package",
  "Title": "IsoBayes: Single Isoform protein inference Method via Bayesian\nAnalyses",
  "Version": "1.11.0",
  "Description": "IsoBayes is a Bayesian method to perform inference on\nsingle protein isoforms. Our approach infers the\npresence/absence of protein isoforms, and also estimates their\nabundance; additionally, it provides a measure of the\nuncertainty of these estimates, via: i) the posterior\nprobability that a protein isoform is present in the sample;\nii) a posterior credible interval of its abundance. IsoBayes\ninputs liquid cromatography mass spectrometry (MS) data, and\ncan work with both PSM counts, and intensities. When available,\ntrascript isoform abundances (i.e., TPMs) are also\nincorporated: TPMs are used to formulate an informative prior\nfor the respective protein isoform relative abundance. We\nfurther identify isoforms where the relative abundance of\nproteins and transcripts significantly differ. We use a\ntwo-layer latent variable approach to model two sources of\nuncertainty typical of MS data: i) peptides may be erroneously\ndetected (even when absent); ii) many peptides are compatible\nwith multiple protein isoforms. In the first layer, we sample\nthe presence/absence of each peptide based on its estimated\nprobability of being mistakenly detected, also known as PEP\n(i.e., posterior error probability). In the second layer, for\npeptides that were estimated as being present, we allocate\ntheir abundance across the protein isoforms they map to. These\ntwo steps allow us to recover the presence and abundance of\neach protein isoform.",
  "Authors@R": "c(person(given = \"Jordy\",\nfamily = \"Bollon\",\nrole = c(\"aut\"),\nemail = \"jordy.bollon@iit.it\"),\nperson(given = \"Simone\",\nfamily = \"Tiberi\",\nrole = c(\"aut\", \"cre\"),\nemail = \"simone.tiberi@unibo.it\",\ncomment = c(ORCID = \"0000-0002-3054-9964\")))",
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  "URL": "https://github.com/SimoneTiberi/IsoBayes",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 13:01:56 UTC",
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  "Author": "Jordy Bollon [aut],\nSimone Tiberi [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-3054-9964>)",
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