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Вызов вариантов×Полногеномное ассоциативное исследование эпигенома (EWAS)×
ОбластьБиоинформатикаБиоинформатика
СемействоProcess / pipelineProcess / pipeline
Год появления2009–2010 (modern high-throughput era)2008–2011 (term and framework established c. 2011)
Автор методаLi et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application
ТипComputational genomics pipelinePopulation-scale epigenomic association study
Основополагающий источникMcKenna, 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 ↗Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529–541. DOI ↗
Другие названияSNP calling, genotyping from sequencing, mutation detection, variant detectionEWAS, methylome-wide association study, epigenetic association study, DNA methylation association study
Связанные65
СводкаVariant 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.An epigenome-wide association study (EWAS) is a hypothesis-free, genome-scale method that systematically tests whether epigenetic marks — predominantly CpG-site DNA methylation — differ between individuals with and without a trait, disease, or exposure. By scanning hundreds of thousands of genomic positions simultaneously, EWAS identifies loci where the epigenome is reproducibly associated with a phenotype, offering a layer of biological regulation that classical GWAS does not capture.
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
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ScholarGateСравнение методов: Variant Calling · Epigenome-wide association study. Получено 2026-06-18 из https://scholargate.app/ru/compare