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분야생물정보학생물정보학
계열Process / pipelineProcess / pipeline
기원 연도2001–20052009–2010 (modern high-throughput era)
창시자Ian Holmes & William J. Bruno; Benjamin Redelings & Marc SuchardLi et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
유형Probabilistic computational methodComputational genomics pipeline
원전Redelings, B. D., & Suchard, M. A. (2005). Joint Bayesian estimation of alignment and phylogeny. Systematic Biology, 54(3), 401–418. 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 ↗
별칭Bayesian MSA, probabilistic sequence alignment, statistical alignment, BAli-Phy alignmentSNP calling, genotyping from sequencing, mutation detection, variant detection
관련56
요약Bayesian sequence alignment treats the alignment of biological sequences (DNA, RNA, or protein) as a probabilistic inference problem rather than a deterministic optimization. Instead of returning a single best alignment, it samples from a posterior distribution over all plausible alignments given a substitution model and gap penalty priors, thereby quantifying alignment uncertainty. It is particularly valuable when downstream analyses such as phylogenetic inference or functional annotation are sensitive to alignment error.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.
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