Summary
A limitation of pooled CRISPR-Cas9 viability screens is the high false-positive rate in detecting essential genes arising from copy number-amplified (CNA) regions of the genome. To solve this issue, we developed CRISPRcleanR: a computational method implemented as R/python package and in a dockerized version. CRISPRcleanR detects and corrects biased responses to CRISPR-Cas9 targeting in an unsupervised fashion, accurately reducing false-positive signals, while maintaining sensitivity in identifying relevant genetic dependencies. Here, we present CRISPRcleanRWebApp, a web-based application enabling access to CRISPRcleanR through an intuitive graphical web-interface. CRISPRcleanRWebApp removes the complexity of low-level R/python-language user interactions; it provides a user-friendly access to a complete analytical pipeline, not requiring any data pre-processing, and generating gene-level summaries of essentiality with associated statistical scores; it offers a range of interactively explorable plots, while supporting a wider range of CRISPR guide RNAs’ libraries with respect to the original package. CRISPRcleanRWebApp is freely available at: https://crisprcleanr-webapp.fht.org/.
Highlights
CRISPR-Cas9 screens are widely used for the identification of cancer dependencies
In such screens, false-positives arise from targeting copy number amplified genes
CRISPRcleanR corrects this bias in an unsupervised fashion
CRISPRcleanRWebApp is a web user-friendly front-end for CRISPRcleanR
Competing Interest Statement
FI receives funding from Open Targets, a public-private initiative involving academia and industry and performs consultancy for the joint CRUK-AstraZeneca Functional Genomics Centre. All other authors declare that they have no competing interests.
Footnotes
We have substantially re-implemented the CRISPRcleanR WebApp architecture, including many additional capabilities, and changes to its graphical user interface. As a result, we are now providing the community with a much more complete and easy-to-use tool, which does not require any data preprocessing and can thus be readily applied to raw sequencing files, returning gene level essentiality summaries with indicators of gene depletion significance, i.e. the final readout of a genome-wide CRISPR-Cas9 screen. Briefly, major changes have involved: -Extending CRISPRcleanRWebApp and its underlying R package CRISPRcleanR to support the processing of raw sequencing files (in FASTQ and BAM format); -Extending CRISPRcleanRWebApp to support the processing of data coming from CRISPR-Cas9 screens performed with any sgRNA library, for which is now enough to upload a library annotation file, in plain tab delimited text format (this feature was already implemented in CRISPRcleanR); -Including the generation of gene-level summaries of essentiality with statistical indicator based on false-discovery-rate of prior known non-essential genes (derived from (Hart and Moffat 2016)) and MAGeCK (a previously published method based on on a mean-variance modelling approach (Li et al. 2014)); -Implementing a robust user-account registration and authentication system that guarantees full data and results' privacy. -Substantially improving the graphical user interface (GUI) of CRISPRcleanRWebApp; -Regenerating all demo-videos and tutorial tips in the home page of CRISPRcleanRWebApp to reflect all the implemented changes; -Updating main figures and text to reflect all the above changes. IMPORTANT: the new URL of CRISPRcleanRWebApp is https://crisprcleanr-webapp.fht.org/
Abbreviations
- API
- application programming interface
- AUPRC
- Area Under Precision-Recall Curve
- AUROC
- Area Under Receiver Operating Characteristic
- CCLE
- Cancer Cell Line Encyclopaedia
- CN
- copy number
- CRISPR
- Clustered Regularly Interspaced Short Palindromic Repeats
- DSB
- double strand breaks
- EG
- essential genes
- FDR
- false discovery rate
- GDSC
- Genomics of Drug Sensitivity in Cancer dataset
- logFC
- log fold-change
- MSigDB
- molecular signature database
- NEG
- nonessential genes
- QC
- quality control
- sgRNA
- single-guide RNA
- PPV
- positive predicted value
- SPA
- Single Page Application