MOTIVATION: Clustered regularly interspaced short palindromic repeats (CRISPR) technologies allow for facile genomic modification in a site-specific manner. A key step in this process is the in silico design of single guide RNAs to efficiently and specifically target a site of interest. To this end, it is necessary to enumerate all potential off-target sites within a given genome that could be inadvertently altered by nuclease-mediated cleavage. Currently available software for this task is limited by computational efficiency, variant support or annotation, and assessment of the functional impact of potential off-target effects. RESULTS: To overcome these limitations, we have developed CRISPRitz, a suite of software tools to support the design and analysis of CRISPR/CRISPR-associated (Cas) experiments. Using efficient data structures combined with parallel computation, we offer a rapid, reliable, and exhaustive search mechanism to enumerate a comprehensive list of putative off-target sites. As proof-of-principle, we performed a head-to-head comparison with other available tools on several datasets. This analysis highlighted the unique features and superior computational performance of CRISPRitz including support for genomic searching with DNA/RNA bulges and mismatches of arbitrary size as specified by the user as well as consideration of genetic variants (variant-aware). In addition, graphical reports are offered for coding and non-coding regions that annotate the potential impact of putative off-target sites that lie within regions of functional genomic annotation (e.g. insulator and chromatin accessible sites from the ENCyclopedia Of DNA Elements [ENCODE] project). AVAILABILITY AND IMPLEMENTATION: The software is freely available at: https://github.com/pinellolab/CRISPRitzhttps://github.com/InfOmics/CRISPRitz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) nuclease system has allowed for high-throughput, large scale pooled screens for functional genomic studies. To aid in the translation of functional genomics to therapeutics, we developed DrugThatGene (DTG) as a web-based application that streamlines analysis of potential therapeutic targets identified from functional genetic screens. RESULTS: Starting from a gene list as input, DTG offers automated identification of small molecules along with supporting information from human genetic and other relevant databases. Furthermore, DTG aids in the identification of common biological pathways and protein complexes in conjunction with associated small molecule inhibitors. Taken together, DTG aims to expedite the identification of small molecules from the abundance of functional genetic data generated from CRISPR screens. AVAILABILITY AND IMPLEMENTATION: DTG is an open-source and free software available as a website at http://drugthatgene.pinellolab.org. Source code is available at: https://github.com/pinellolab/DrugThatGene, which can be downloaded in order to run DTG locally.