Novel bioinformatics quality control metric for next-generation sequencing experiments in the clinical context.

ABSTRACT: As the use of next-generation sequencing (NGS) for the Mendelian diseases diagnosis is expanding, the performance of this method has to be improved in order to achieve higher quality. Typically, performance measures are considered to be designed in the context of each application and, therefore, account for a spectrum of clinically relevant variants. We present EphaGen, a new computational methodology for bioinformatics quality control (QC). Given a single NGS dataset in BAM format and a pre-compiled VCF-file of targeted clinically relevant variants it associates this dataset with a single arbiter parameter. Intrinsically, EphaGen estimates the probability to miss any variant from the defined spectrum within a particular NGS dataset. Such performance measure virtually resembles the diagnos

SUBMITTER: Ivanov M 

PROVIDER: S-EPMC6868350 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature