قارن الطرق

	استدعاء المتغيرات	دراسة الارتباط على مستوى الجينوم الفوقي (EWAS)
المجال	المعلوماتية الحيوية	المعلوماتية الحيوية
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	2009–2010 (modern high-throughput era)	2008–2011 (term and framework established c. 2011)
صاحب الطريقة	Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)	Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application
النوع	Computational genomics pipeline	Population-scale epigenomic association study
المصدر التأسيسي	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.	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.
الأسماء البديلة	SNP calling, genotyping from sequencing, mutation detection, variant detection	EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study
ذات صلة	6	5
الملخص	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.	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.