Comparer des méthodes

	Analyse phylogénétique de séries temporelles	Appel de variants
Domaine	Bio-informatique	Bio-informatique
Famille	Process / pipeline	Process / pipeline
Année d'origine	2000s (molecular clock methods earlier; BEAST framework 2007)	2009–2010 (modern high-throughput era)
Auteur d'origine	Alexei J. Drummond, Andrew Rambaut, and colleagues	Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
Type	Evolutionary bioinformatics pipeline	Computational genomics pipeline
Source fondatrice	Drummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7, 214.	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.
Alias	temporal phylogenetics, time-resolved phylogenetics, molecular clock phylogenetics, phylodynamics	SNP calling, genotyping from sequencing, mutation detection, variant detection
Apparentées	6	6
Résumé	Time-series phylogenetic analysis reconstructs the evolutionary history of organisms or genetic variants using sequences sampled at known time points. By incorporating sampling dates directly into the model, it estimates divergence times, substitution rates, and ancestral relationships on an absolute timescale — making it essential for studying viral outbreaks, ancient DNA dynamics, and rapid microbial evolution.	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.