MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants
Summary: 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 bee...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019-08-01
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| Series: | iScience |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004219302366 |
| _version_ | 1818174153366175744 |
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| author | Luca Denti Marco Previtali Giulia Bernardini Alexander Schönhuth Paola Bonizzoni |
| author_facet | Luca Denti Marco Previtali Giulia Bernardini Alexander Schönhuth Paola Bonizzoni |
| author_sort | Luca Denti |
| collection | DOAJ |
| description | Summary: 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 Subject Areas: Biological Sciences, Genetics, Genomics, Bioinformatics |
| first_indexed | 2024-12-11T19:39:52Z |
| format | Article |
| id | doaj.art-a8e4ae07fe46401f822bda198b458145 |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-12-11T19:39:52Z |
| publishDate | 2019-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-a8e4ae07fe46401f822bda198b4581452022-12-22T00:53:02ZengElsevieriScience2589-00422019-08-01182027MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriantsLuca Denti0Marco Previtali1Giulia Bernardini2Alexander Schönhuth3Paola Bonizzoni4Department of Computer Sciences, Systems and Communications, University of Milan-Bicocca, Piazza dell’Ateneo Nuovo, 1, 20126 Milan, ItalyDepartment of Computer Sciences, Systems and Communications, University of Milan-Bicocca, Piazza dell’Ateneo Nuovo, 1, 20126 Milan, Italy; Corresponding authorDepartment of Computer Sciences, Systems and Communications, University of Milan-Bicocca, Piazza dell’Ateneo Nuovo, 1, 20126 Milan, ItalyCentrum Wiskunde & Informatica, Science Park 123, 1098 XG Amsterdam, The NetherlandsDepartment of Computer Sciences, Systems and Communications, University of Milan-Bicocca, Piazza dell’Ateneo Nuovo, 1, 20126 Milan, ItalySummary: 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 Subject Areas: Biological Sciences, Genetics, Genomics, Bioinformaticshttp://www.sciencedirect.com/science/article/pii/S2589004219302366 |
| spellingShingle | Luca Denti Marco Previtali Giulia Bernardini Alexander Schönhuth Paola Bonizzoni MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants iScience |
| title | MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants |
| title_full | MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants |
| title_fullStr | MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants |
| title_full_unstemmed | MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants |
| title_short | MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants |
| title_sort | malva genotyping by mapping free allele detection of known variants |
| url | http://www.sciencedirect.com/science/article/pii/S2589004219302366 |
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