Variantanalys

Variantanalys is the process of identifying, annotating and interpreting genetic variants discovered through DNA sequencing to determine their potential impact on phenotype or disease. It encompasses data processing, evidence gathering and clinical or research interpretation to inform decisions or hypotheses.

Typical data sources are whole-genome sequencing, whole-exome sequencing, or targeted gene panels. The workflow includes read alignment to a reference genome, variant calling to detect SNPs and indels, and quality control to reduce false positives. The final product is usually a Variant Call Format (VCF) file, which lists detected variants and associated metrics.

Annotation assigns biological context to each variant by linking it to genes, regulatory elements and known variant databases such as dbSNP, ClinVar and population resources like gnomAD. Interpretation uses evidence from functional predictions (such as SIFT, PolyPhen, CADD), conservation, segregation data, and clinical guidelines such as ACMG/AMP to classify variants as pathogenic, likely pathogenic, uncertain significance, likely benign, or benign.

Applications include clinical diagnostics and prognosis, pharmacogenomics, and research into disease mechanisms. In clinical practice, variantanalys informs diagnostic decisions, risk assessment and sometimes treatment choices; in research it supports genotype–phenotype associations and functional studies.

Challenges include handling variants of uncertain significance, biases from limited population diversity, data privacy, and the need for reproducible pipelines and standardized reporting. Ethical considerations cover informed consent, incidental findings and the appropriate return of results.

Common tools and formats used in variantanalys include alignment and variant-calling pipelines (for example, BWA, GATK, FreeBayes), and annotation tools (VEP/Ensembl, ANNOVAR). Outputs typically involve FASTQ, BAM/CRAM and VCF files, along with comprehensive variant interpretation reports.