A new approach (EDIZ) for big data variant prioritization

Autor:	Mehmet Ali Ergun, Sezen Guntekin Ergun, E. Ferda Percin
Rok vydání:	2019
Předmět:	Prioritization 0303 health sciences business.industry Computer science Urology Big data Data science Health informatics 03 medical and health sciences Annotation 0302 clinical medicine Workflow 030220 oncology & carcinogenesis business Raw data Indel Exome sequencing 030304 developmental biology
Zdroj:	Network Modeling Analysis in Health Informatics and Bioinformatics. 8
ISSN:	2192-6670 2192-6662
Popis:	Whole exome sequencing (WES), workflow consists of the following steps: raw data quality assessment, pre-processing, alignment, post-processing, variant calling, annotation, and prioritization. WES of human samples was reported to detect approximately 20,000-30,000 SNV and indel calls on average. Therefore, it is very important to choose the best tool that suits the related study. In this study, we aimed to upgrade our previous in-house variant prioritization method to analyse WES data without using in silico methods. By this method, the annotated data have been decreased by means of 52.3 times. Therefore, we both established a successful WES workflow for increasing the diagnostic rate of patients with reducing the raw data. Recently, we are also building a web-based workflow to help the users from all over the world.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::958b13e50cf9802287ca49b6d55a1ca4 https://doi.org/10.1007/s13721-019-0197-1 Zobrazit plný text záznamu Full text from SpringerLink