方法对比

	基于网络的变异检测	变异检测
领域	生物信息学	生物信息学
方法族	Process / pipeline	Process / pipeline
起源年份	2017–2018	2009–2010 (modern high-throughput era)
提出者	Erik Garrison, Paten lab (UCSC); Hannes Eggertsson, deCODE Genetics	Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
类型	Computational genomics pipeline	Computational genomics pipeline
开创性文献	Garrison, E., Sirén, J., Novak, A. M., Hickey, G., Eizenga, J. M., Dawson, E. T., Jones, W., Garg, S., Markello, C., Lin, M. F., Paten, B., & Durbin, R. (2018). Variation graph toolkit improves read mapping by representing genetic variation in the reference. Nature Biotechnology, 36(9), 875–879.	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.
别名	graph-genome variant calling, variation graph genotyping, vg-based variant calling, pangenome variant calling	SNP calling, genotyping from sequencing, mutation detection, variant detection
相关	6	6
摘要	Network-based (graph-genome) variant calling replaces the conventional single linear reference genome with a variation graph — a network in which nodes represent sequence segments and edges represent known alternative paths through the genome. Reads are mapped onto this graph, enabling detection of SNPs, indels, and structural variants with substantially lower reference bias than linear-reference pipelines. Key tools include the Variation Graph Toolkit (vg) and Graphtyper.	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.