Zobraziť v EDS

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

Uložené v:
Podrobná bibliografia
Názov: Comparing variant calling tools for genomic analysis of patients predisposed to Kidney Disease
Autori: Neuwirthová, Jana, Indráková, Jana, Provazník, Valentýna, Schwarzerová, Jana
Informácie o vydavateľovi: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2025.
Rok vydania: 2025
Predmety: next generation sequencing, Variant calling tools, kidney disease, genetic variants
Popis: 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 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.
Druh dokumentu: Conference object
Popis súboru: text; application/pdf
Jazyk: English
Prístupová URL adresa: https://hdl.handle.net/11012/255287
Prístupové číslo: edsair.od......2852..862104b7361d113d6dc9f85ddf4d844a
Databáza: OpenAIRE
Popis
Abstrakt: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 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.