GrassSV - hybrid method to detect structural variants in high throughput DNA-seq data.
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| Title: | GrassSV - hybrid method to detect structural variants in high throughput DNA-seq data. |
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| Authors: | Witczak D; Institute of Computing Science, Poznan University of Technology, Poznan, Poland.; ECBiG, European Center of Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland., Sychla K; Institute of Computing Science, Poznan University of Technology, Poznan, Poland., Wysocka J; Institute of Computing Science, Poznan University of Technology, Poznan, Poland., Laskowski A; Institute of Computing Science, Poznan University of Technology, Poznan, Poland.; ECBiG, European Center of Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland., Frohmberg W; Institute of Computing Science, Poznan University of Technology, Poznan, Poland.; ECBiG, European Center of Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland., Glowacka M; Institute of Computing Science, Poznan University of Technology, Poznan, Poland., Dzik A; Institute of Computing Science, Poznan University of Technology, Poznan, Poland.; ECBiG, European Center of Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland., Lukasiak P; Institute of Computing Science, Poznan University of Technology, Poznan, Poland.; ECBiG, European Center of Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland., Blazewicz J; Institute of Computing Science, Poznan University of Technology, Poznan, Poland.; ECBiG, European Center of Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland.; Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland., Swiercz A; Institute of Computing Science, Poznan University of Technology, Poznan, Poland.; ECBiG, European Center of Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland.; Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2026 Jun 22; Vol. 22 (6), pp. e1014406. Date of Electronic Publication: 2026 Jun 22 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1014406 |
