A graph clustering algorithm for detection and genotyping of structural variants from long reads

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dc.contributor.authorNicolás Gaitán
dc.contributor.authorJorge Duitama
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T15:18:39Z
dc.date.available2026-03-22T15:18:39Z
dc.date.issued2023
dc.descriptionCitaciones: 3
dc.description.abstractThe results show that our approach outperformed state-of-the-art tools on germline SV calling and genotyping, especially at low depths, and in error-prone repetitive regions. We believe this work significantly contributes to the development of bioinformatic strategies to maximize the use of long-read sequencing technologies.
dc.identifier.doi10.1093/gigascience/giad112
dc.identifier.urihttps://doi.org/10.1093/gigascience/giad112
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/51622
dc.language.isoen
dc.publisherUniversity of Oxford
dc.relation.ispartofGigaScience
dc.sourceUniversidad de Los Andes
dc.subjectStructural variation
dc.subjectCluster analysis
dc.subjectGenotyping
dc.subjectComputational biology
dc.subjectComputer science
dc.subjectGenomics
dc.subjectAlgorithm
dc.subjectBiology
dc.subjectGenome
dc.subjectData mining
dc.titleA graph clustering algorithm for detection and genotyping of structural variants from long reads
dc.typearticle

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