New computational tool improves gene identification
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.