Comparing variant calling tools for genomic analysis of patients predisposed to Kidney Disease

but.event.date29.04.2025cs
but.event.titleSTUDENT EEICT 2025cs
dc.contributor.authorNeuwirthová, Jana
dc.contributor.authorIndráková, Jana
dc.contributor.authorProvazník, Valentýna
dc.contributor.authorSchwarzerová, Jana
dc.date.accessioned2025-07-30T10:00:57Z
dc.date.available2025-07-30T10:00:57Z
dc.date.issued2025cs
dc.description.abstractThis study compares various variant calling tools for the analysis of genomic data from patients predisposed to kidney disease and evaluates algorithms for identifying genetic variants that may contribute to the pathogenesis of these conditions. The aim is to assess the performance of these tools, focusing on their sensitivity and specificity in detecting specific pathogenic variants. The study tests three variant calling tools on genomic data from four selected patient s sequenced at the University Hospital Ostrava. It compares different variant calling approaches, emphasizing their impact on the accuracy and efficiency of identifying relevant genetic variants. The tools were selected based on their widespread usage, strong benchmarking performance in prior studies, and compatibility with the Sarek pipeline, making them the most modern approaches in variant calling, suitable for both research and clinical applications. As part of this study, high-throughput sequencing data will be analysed, and methods for variant detection will be evaluated at different levels of precision and sensitivity.en
dc.formattextcs
dc.format.extent226-230cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings I of the 31st Conference STUDENT EEICT 2025: General papers. s. 226-230. ISBN 978-80-214-6321-9cs
dc.identifier.isbn978-80-214-6321-9
dc.identifier.urihttps://hdl.handle.net/11012/255287
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 31st Conference STUDENT EEICT 2025: General papersen
dc.relation.urihttps://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2025_sbornik_1.pdfcs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectVariant calling toolsen
dc.subjectkidney diseaseen
dc.subjectnext generation sequencingen
dc.subjectgenetic variantsen
dc.titleComparing variant calling tools for genomic analysis of patients predisposed to Kidney Diseaseen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs

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