Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Сетевой вызов вариантов× | Вызов вариантов× | |
|---|---|---|
| Область | Биоинформатика | Биоинформатика |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2017–2018 | 2009–2010 (modern high-throughput era) |
| Автор метода≠ | Erik Garrison, Paten lab (UCSC); Hannes Eggertsson, deCODE Genetics | Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010) |
| Тип | Computational genomics pipeline | Computational genomics pipeline |
| Основополагающий источник≠ | 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. 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 ↗ |
| Другие названия | graph-genome variant calling, variation graph genotyping, vg-based variant calling, pangenome variant calling | SNP calling, genotyping from sequencing, mutation detection, variant detection |
| Связанные | 6 | 6 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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