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贝叶斯变异检测×变异检测×
领域生物信息学生物信息学
方法族Process / pipelineProcess / pipeline
起源年份2010 (GATK framework); Bayesian genotyping principles preceded by Samtools/MAQ ~2008–20092009–2010 (modern high-throughput era)
提出者Mark DePristo, Eric Banks, and the Broad Institute GATK teamLi et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
类型Probabilistic genomic inference pipelineComputational genomics pipeline
开创性文献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 ↗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 ↗
别名Bayesian genotyping, probabilistic variant calling, GATK HaplotypeCaller, Bayesian SNP/indel detectionSNP calling, genotyping from sequencing, mutation detection, variant detection
相关66
摘要Bayesian variant calling is a computational pipeline that uses probabilistic inference to identify single-nucleotide polymorphisms (SNPs), insertions, and deletions in a genome by treating sequencing data as evidence and computing posterior probabilities over candidate genotypes. Unlike deterministic threshold-based callers, Bayesian approaches explicitly model sequencing error, mapping uncertainty, and prior genotype frequencies to produce calibrated genotype likelihoods that can be used for downstream filtering and association testing.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.
ScholarGate数据集
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  2. 2 来源
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  1. v1
  2. 2 来源
  3. PUBLISHED

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ScholarGate方法对比: Bayesian Variant Calling · Variant Calling. 于 2026-06-17 检索自 https://scholargate.app/zh/compare