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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0197919" target="_blank" >RIV/00216305:26220/26:0197919 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2025_sbornik_1.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2025_sbornik_1.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

This 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 patients 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.

Název v anglickém jazyce

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

Popis výsledku anglicky

This 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 patients 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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings I of the 31st Conference STUDENT EEICT 2025

ISBN

978-80-214-6321-9

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

226-230

Název nakladatele

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Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

29. 4. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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