Variant Calling is a crucial step in identifying genetic variations that may contribute to diseases or impact drug efficacy. It involves analyzing DNA sequencing data to identify changes in the DNA sequence, such as single nucleotide polymorphisms (SNPs) or insertions/deletions (Indels). This can be done for the whole genome, whole exome, or targeted regions of interest.
Germline variant calling involves comparing the individual’s DNA sequence to a standard reference genome for the species of interest, allowing for the identification of genotypes. In contrast, somatic variant calling uses a related tissue from the same individual as a reference, allowing for the identification of genetic mosaicism between cells. Somatic variant calling is particularly important in cancer research, where it can help identify mutations that occur in tumor cells but not in normal cells.
Accurate variant calling is essential for many applications, such as genetic disease diagnosis, personalized medicine, and drug discovery. By identifying disease-causing mutations or genetic variations that may affect drug response, variant calling can inform treatment decisions and help advance precision medicine. Moreover, with the development of new sequencing technologies, such as long-read sequencing, variant calling is becoming increasingly accurate and can identify novel and complex genetic variations that were previously difficult to detect.
- Quality control: assessing the quality of raw sequencing data and filtering out low-quality reads.
- Alignment: mapping the reads to a reference genome or transcriptome.
- Variant calling: identifying genetic variants from aligned reads.
- Annotation: annotating variants with information such as their location, type, and functional impact.
Possible downstream tasks:
- Filtering: removing low-quality variants, variants with low allele frequencies, or variants in non-coding regions.
- Prioritization: prioritizing variants based on their functional impact, such as those affecting protein-coding regions or known disease-associated genes.
- Population genetics: analyzing the frequency and distribution of genetic variants across different populations to gain insights into human evolution and disease susceptibility.
- Functional analysis: predicting the functional impact of variants on protein structure, gene expression, or regulatory mechanisms.
- Precision medicine: using genetic variants to inform diagnosis, treatment, and prognosis of patients with genetic diseases.
The number of downstream analyses that become available is constantly expanding and Karda Genomics supports all recent approaches.