New computational tool improves identification of genes of potential clinical significance

Like finding a needle in a haystack, identifying genes that are involved in particular diseases can be an arduous and time consuming process. Looking to improve this process, a team led by researchers at Baylor College of Medicine has developed a new bioinformatics tool that analyzes CRISPR pooled screen data and identifies candidates for potentially relevant genes with greater sensitivity and accuracy than other existing methods. The new analytical web-based tool also is quicker and more user friendly as it does not require bioinformatics training to use it. The study appears in the journal Genome Research.

source https://www.lifetechnology.com/blogs/life-technology-news-blog/new-computational-tool-improves-identification-of-genes-of-potential-clinical-significance