VIVIDHA: Variant Prediction and Visualization Interface for Dynamic High-throughput Analysis

Large scale genome sequencing projects have produced huge datasets that pose challenges of high processing times especially for variant calling, a significant downstream analysis step. Efficient utilization of computational resources for accurate variant prediction in a timely manner is possible using Hadoop MapReduce framework. We have developed VIVIDHA (Variant Prediction and Visualization Interface for Dynamic High-throughput Analysis), a high throughput methodology for prediction of variants based on splitting the alignment file using overlapping regions using Hadoop MapReduce framework. The size of overlap region is user-defined. Three variant callers viz. GATK, VarScan2 and BCFTools have been included to predict variants using a consensus approach. Speed-up observed provides the rationale of better performance as number of compute cores and file size are increased. VIVIDHA is available in both GUI as well as command-line modes and can be downloaded from URL: https://github.com/bioinformatics-cdac/VividhaInstaller