方法对比

	基于网络的变异检测	序列比对
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	1970 (global alignment); 1981 (local alignment)
提出者	Erik Garrison, Paten lab (UCSC); Hannes Eggertsson, deCODE Genetics	Saul B. Needleman & Christian D. Wunsch (global); Temple F. Smith & Michael S. Waterman (local)
类型	Computational genomics pipeline	Computational sequence analysis technique
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.	Needleman, S. B., & Wunsch, C. D. (1970). A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology, 48(3), 443–453.
别名	graph-genome variant calling, variation graph genotyping, vg-based variant calling, pangenome variant calling	pairwise alignment, multiple sequence alignment, MSA, sequence comparison
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.	Sequence alignment is a foundational bioinformatics technique that arranges two or more DNA, RNA, or protein sequences to reveal regions of similarity, infer evolutionary relationships, identify functional domains, and map sequencing reads to reference genomes. It underpins virtually every downstream genomic analysis, from variant calling and gene expression quantification to phylogenetics and structural annotation.