Annotating the genomic variants in Next Generation Sequencing data through computational approach

Abstract

Next Generation Sequencing (NGS) has made possible the parallel analysis of sequencing data. Different NGS platforms are generating huge amount of data. This data undergoes different analysis pipeline depending upon the platform from which it is produced. Bioinformatics has made this analysis easier by the development of different tools and pipelines. Several pipelines are available for performing different types of analysis which includes variant calling, phylogenetic analysis and many others. In variant calling, once the variants have been called, it is important to identify their biological significance and their location in the genome. This can be helpful to identify their roles in different disease. Several tools are available for this purpose. Each tool has its own features, with certain limitations. Some tools require the annotation sets from the user, while others require programming skills to use it. So, an automated pipeline is required to overcome these limitations. This thesis provides the detail about an automated pipeline implemented in R programming language named as AutoAnnotate. AutoAnnotate takes only the VCF file as an input and generates the annotation results for the user, along with different charts and tables representing annotation information in different ways.