Võrdle meetodeid

	Bayesian Sequence Alignment	Variant Calling
Valdkond	Bioinformaatika	Bioinformaatika
Perekond	Process / pipeline	Process / pipeline
Tekkeaasta	2001–2005	2009–2010 (modern high-throughput era)
Looja	Ian Holmes & William J. Bruno; Benjamin Redelings & Marc Suchard	Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
Tüüp	Probabilistic computational method	Computational genomics pipeline
Algallikas	Redelings, B. D., & Suchard, M. A. (2005). Joint Bayesian estimation of alignment and phylogeny. Systematic Biology, 54(3), 401–418.	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.
Rööpnimetused	Bayesian MSA, probabilistic sequence alignment, statistical alignment, BAli-Phy alignment	SNP calling, genotyping from sequencing, mutation detection, variant detection
Seotud	5	6
Kokkuvõte	Bayesian 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.