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  "Title": "Differentially Methylated Cytosines via a Bayesian Functional\nApproach",
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  "Authors@R": "c(person(\"Farhad\", \"Shokoohi\", role = c(\"aut\", \"cre\"),\nemail = \"shokoohi@icloud.com\", comment = c(ORCID = \"0000-0002-6224-2609\"))\n)",
  "Description": "DMCFB is a pipeline for identifying differentially\nmethylated cytosines using a Bayesian functional regression\nmodel in bisulfite sequencing data. By using a functional\nregression data model, it tries to capture position-specific,\ngroup-specific and other covariates-specific methylation\npatterns as well as spatial correlation patterns and unknown\nunderlying models of methylation data. It is robust and\nflexible with respect to the true underlying models and\ninclusion of any covariates, and the missing values are imputed\nusing spatial correlation between positions and samples. A\nBayesian approach is adopted for estimation and inference in\nthe proposed method.",
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  "Date/Publication": "2026-04-28 12:51:04 UTC",
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