CReSCENT: CanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users.

The International Mouse Phenotyping Consortium (IMPC) is generating and phenotyping null mutations for every protein-coding gene in the mouse. The IMPC now uses Cas9, a programmable RNA-guided nuclease that has revolutionized mouse genome editing and increased capacity and flexibility to efficiently generate null alleles in the C57BL/6N strain. In addition to being a valuable novel and accessible research resource, the production of >3,300 knockout mouse lines using comparable protocols provides a rich dataset to analyze experimental and biological variables affecting in vivo null allele engineering with Cas9. Mouse line production has two critical steps - generation of founders with the desired allele and germline transmission (GLT) of that allele from founders to offspring. Our analysis identified that whether a gene is essential for viability was the primary factor influencing successful production of null alleles. Collectively, our findings provide best practice recommendations for generating null alleles in mice using Cas9; these recommendations may be applicable to other allele types and species.

CReSCENT: CanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users.

Cas-mediated genome editing has enabled researchers to perform mutagenesis experiments with relative ease. Effective genome editing requires tools for guide RNA selection, off-target prediction, and genotyping assay design. While independent tools exist for these functions, there is still a need for a comprehensive platform to design, view, evaluate, store, and catalogue guides and their associated primers. The Finding Optimizing and Reporting Cas Targets (FORCAST) application integrates existing open source tools such as JBrowse, Primer3, BLAST, bwa, and Silica to create a complete allele design and quality assurance pipeline. FORCAST is a fully integrated software that allows researchers performing Cas-mediated genome editing to generate, visualize, store, and share information related to guides and their associated experimental parameters. It is available from a public GitHub repository and as a Docker image, for ease of installation and portability.