Decoding Retinoblastoma: Unraveling Genetic Variants Through Bioinformatics and Next-Generation Sequencing Data Analysis

Next-generation sequencing platforms generate massive amounts of raw sequencing data which are processed using bioinformatics tools. This research study presents a comprehensive analysis of whole genome sequencing (WGS) data and evolutionary insights into retinoblastoma variants. The study leverages WGS data obtained from three Indian retinoblastoma patient samples, employing advanced bioinformatics tools to uncover genetic alterations and assess their potential linkage with predisposition to the disease. We extracted the data available in public repositories like NCBI SRA and employed a combination of bioinformatics softwares, web services, and tools focusing on mutation analysis. We sketched a common pipeline and followed all the methodologies to process the samples. The results shed light on the driver genes, shared mutations, and key pathways across the samples.