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21 methods in this family.

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Bayesian ChIP-seq peak callingBayesian ChIP-seq peak calling applies probabilistic models — typically Poisson, negative binomial, or hidden Markov models with Bayesian inference — to detect genomic regions enriBayesian Copy Number Variation AnalysisBayesian copy number variation (CNV) analysis is a probabilistic framework for detecting genomic segments where an individual's DNA copy count deviates from the diploid norm. By plBayesian epigenome-wide association studyA Bayesian EWAS is a genome-scale association analysis that links epigenetic marks — most commonly CpG-site DNA methylation — to a phenotype or trait of interest, replacing or suppBayesian epigenome-wide association study in educational researchA Bayesian epigenome-wide association study (Bayesian EWAS) scans hundreds of thousands of DNA methylation sites across the genome to identify those statistically associated with aBayesian eQTL analysisBayesian eQTL analysis identifies genetic variants (eQTLs) that regulate gene expression by combining genotype and RNA-seq data within a probabilistic framework. Unlike frequentistBayesian Gene Set Enrichment AnalysisBayesian gene set enrichment analysis (Bayesian GSEA) applies a probabilistic framework to determine whether predefined sets of genes — representing biological pathways, cellular p

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This topic's most-referenced foundational methods, in the order they were developed — a place to start if you're new here.

  1. Bayesian Phylogenetic Analysis1996–2001by Rannala & Yang (1996); operationalized by Huelsenbeck et al. (MrBayes, 2001)
  2. Bayesian eQTL analysis2000s–2010sby Matthew Stephens, David J. Balding (Bayesian framework for genetic association); extended by multiple groups for eQTL context
  3. Bayesian Gene Set Enrichment Analysis2004–2007by Michael A. Newton, Frank A. Quintana and colleagues; building on Subramanian et al. GSEA framework
  4. Bayesian Metabolomics Analysis2005–2010by Simon Rogers, Mark Girolami and colleagues (Bayesian NMR metabolomics framework, ~2009); broader Bayesian metabolomics developed through 2000s–2010s
  5. Bayesian GWAS2007–2009 (formal statistical framework)by Matthew Stephens, David J. Balding, Jon Wakefield (key formalizers ca. 2007–2009)
  6. Bayesian RNA-seq differential expression2010–2013by Kendziorski et al. (EBSeq); Hardcastle & Kelly (baySeq)
  7. Bayesian Variant Calling2010 (GATK framework); Bayesian genotyping principles preceded by Samtools/MAQ ~2008–2009by Mark DePristo, Eric Banks, and the Broad Institute GATK team
  8. SIAR Mixing Model2010by Andrew Parnell
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All methods 21

Bayesian ChIP-seq peak callingBayesian Copy Number Variation AnalysisBayesian epigenome-wide association studyBayesian epigenome-wide association study in educational researchBayesian eQTL analysisBayesian Gene Set Enrichment AnalysisBayesian genome-wide association study in educational researchBayesian GWASBayesian Metabolomics AnalysisBayesian Microbiome Diversity AnalysisBayesian Pathway Enrichment AnalysisBayesian Phylogenetic AnalysisBayesian Proteomics AnalysisBayesian RNA-seq differential expressionBayesian Sequence AlignmentBayesian single-cell RNA-seq analysisBayesian Variant CallingFreeze-Drying (Lyophilization)Life Table Response ExperimentNetwork-based gene set enrichment analysisSIAR Mixing Model

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