A new approach (EDIZ) for big data variant prioritization

被引:0
|
作者
Mehmet Ali Ergun
Sezen Guntekin Ergun
E. Ferda Percin
机构
[1] Gazi University Faculty of Medicine,Department of Medical Genetics
[2] Hacettepe University Faculty of Medicine,Department of Medical Biology
来源
Network Modeling Analysis in Health Informatics and Bioinformatics | 2019年 / 8卷
关键词
Whole exome sequencing; Variant prioritization; Data set;
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摘要
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.
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