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Analyse bayésienne de l'expression différentielle en RNA-seq×Appel de variants×
DomaineBio-informatiqueBio-informatique
FamilleProcess / pipelineProcess / pipeline
Année d'origine2010–20132009–2010 (modern high-throughput era)
Auteur d'origineKendziorski et al. (EBSeq); Hardcastle & Kelly (baySeq)Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
TypeBayesian statistical inference pipelineComputational genomics pipeline
Source fondatriceLeng, N., Dawson, J. A., Thomson, J. A., Ruotti, V., Rissman, A. I., Smits, B. M., Haag, J. D., Gould, M. N., Stewart, R. M., & Kendziorski, C. (2013). EBSeq: An empirical Bayes hierarchical model for inference in RNA-seq experiments. Bioinformatics, 29(8), 1035–1043. link ↗McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., ... & DePristo, M. A. (2010). The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), 1297–1303. DOI ↗
AliasBayesian DE analysis, Bayesian RNA-seq DE, baySeq, EBSeqSNP calling, genotyping from sequencing, mutation detection, variant detection
Apparentées66
RésuméBayesian RNA-seq differential expression analysis applies hierarchical Bayesian models to RNA sequencing read-count data to identify genes whose expression levels differ significantly between biological conditions. Rather than relying solely on p-values, these methods quantify the posterior probability that a gene is differentially expressed, borrowing statistical strength across genes and naturally accommodating low sample sizes common in genomics experiments.Variant calling is the computational process of identifying positions in a sequenced genome that differ from a reference sequence — including single nucleotide polymorphisms (SNPs), small insertions and deletions (indels), and structural variants. It transforms aligned sequencing reads into an interpretable catalogue of genetic differences, forming the foundation for population genetics, disease-gene discovery, and clinical genomics applications.
ScholarGateJeu de données
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  2. 2 Sources
  3. PUBLISHED
  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: Bayesian RNA-seq differential expression · Variant Calling. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare