Genome-wide association studies (GWAS) are useful in genetics as they test for the association of a phenotype with common genetic variants. GWAS is “hypothesis-free” and does not require prior knowledge of a gene’s biological impact on a trait. The catch though is that this leads to analyzing hundreds to thousands of genome-wide array samples to elucidate single nucleotide polymorphisms (SNPs) associated with a specific phenotype.
As VarSeq continues its adoption amongst clinical labs and researchers looking for reproducible workflows for variant annotation, filtering and interpretation, we have continued to prioritize the addition of features to assess the quality of the upstream data at a variant, coverage and now sample level. The Importance of Quality Assurance Sample prep and sequencing problems are difficult to detect through the analysis… Read more »