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February 1st, 2025
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Centre for Development of Advanced Computing
bioinformatics
biorxiv

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

Barasiya, T.Open in Google Scholar•Bharti, N.Open in Google Scholar•Gadhari, R.Open in Google Scholar•Bayaskar, A.Open in Google Scholar•Jain, S.Open in Google Scholar•Saxena, A.Open in Google Scholar•Kasibhatla, S. M.Open in Google Scholar•Joshi, R.Open in Google Scholar

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

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