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MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants
- Publication Year :
- 2019
-
Abstract
- The amount of genetic variation discovered in human populations is growing rapidly leading to challenging computational tasks, such as variant calling. Standard methods for addressing this problem include read mapping, a computationally expensive procedure; thus, mapping-free tools have been proposed in recent years. These tools focus on isolated, biallelic SNPs, providing limited support for multi-allelic SNPs and short insertions and deletions of nucleotides (indels). Here we introduce MALVA, a mapping-free method to genotype an individual from a sample of reads. MALVA is the first mapping-free tool able to genotype multi-allelic SNPs and indels, even in high-density genomic regions, and to effectively handle a huge number of variants. MALVA requires one order of magnitude less time to genotype a donor than alignment-based pipelines, providing similar accuracy. Remarkably, on indels, MALVA provides even better results than the most widely adopted variant discovery tools. Biological Sciences; Genetics; Genomics; Bioinformatics
Details
- Database :
- OAIster
- Notes :
- ELETTRONICO, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1308929573
- Document Type :
- Electronic Resource