A user-oriented software for filtering and prioritizing exome variant datasets
The researchers at University of Michigan have developed a web-based software to filter and prioritize exome variant datasets to extract user-specific results. This software has specific novel filters to identify genetic variants in tumor tissues or disease affected family members. It allows multi-sample comparisons to reveal unique or common variants across multiple samples. It facilitates variants comparison with public database and enhances the user experience by allowing prioritizing the results based on variant functional impact. With this tool, sequencing data analyst and researchers can easily adjust the criteria to visualize the genes of interests. It not only significantly reduces the time to generate customized results, but also minimizes the chance of error by decreasing manual intervention and guarantees the quality of results.
Efficiency of generating exome data analysis is limited by filtering pipeline output to meet customized needs Next generation sequencing technology significantly decreases the cost of sequencing, which enables its usage in a wide range of areas including whole genome sequencing, exome sequencing, CHIP, RNA sequencing, metagenomics and so on. It is estimated that the next generation sequencing services market will grow at a compound annual growth rate of 28.0 percent from 2011–2016. Among all applications, clinical related analysis, including the discovery of genetic variants in inherited disorders and cancer, is one of the most important market drivers. Although the process of identifying genetic variants from exome sequencing data is mature and fully automated, the process of sifting through the large dataset of variants to generate customized results is still largely performed manually, causing this step to become rate-limiting step in generating exome data analysis.
Applications • A web-based software to filter and prioritize exome variant datasets to extract user-specific results.
Advantages • Improve efficiency to generate customized analysis • Save time and return results faster • Provide flexible framework to meet a diverse customer requirements • Reduce the need of hiring professional bioinformatics to compose or edit scripts for each analysis • Allow investigators to directly filter results with just a few clicks