Implementation and Optimization of Annotation and Interpretation Step of Next-Generation Sequencing Data for Non-Syndromic Autosomal Recessive Hearing Loss

Introduction: The precision and time required for analysis of data in next-generation sequencing (NGS) depends on many factors including the tools utilized for alignment, variant calling, annotation and filtering of variants, personnel expertise in data analysis and interpretation, and computational capacity of the lab and its optimization is a challenging task.  Method: An application software was designed and implemented in C# for optimizing the third step of NGS data analysis. In this study, annotation, filtering, and interpretation of NGS data were specifically optimized for non-syndromic autosomal recessive hearing loss disease. Results: Whole-exome sequencing data of a patient with a pathogenic mutation confirmed by familial genetic analysis, which contained a total number of 671829 variants after primary analysis, were evaluated by the implemented software. After filtering the variants based on a predefined BED file, 508 variants remained. According to the patient’s pedigree, in the next step of analysis, homozygote variants were selected and only 187 variants remained. After applying the population frequency threshold of 0.6% on gnomeAD and ExAC databases, the number of variants reached 110 and 3, respectively. The identified pathogen was approved by the results of Sanger sequencing done for family co-segregation. This analysis took about 15 minutes on a moderate PC. Conclusion: The designed software is a fully graphical one that has the capability of comparing, viewing, filtering, and merging input files without any coding. Moreover, it can construct a local database from the analyzed files and apply region constraints and user-defined thresholds on various fields of the database.