“…The ability to discriminate prior known essential and non-essential genes based on their depletion LFC observed in a CRISPR-Cas9 recessive screen is widely used to assess the quality of that screen 3,5,7,9,10,23,26,27 .…”
Genome-wide recessive genetic screens using lentiviral CRISPR-guide RNA libraries are widely performed in mammalian cells to functionally characterise individual genes and for the discovery of new anti-cancer therapeutic targets. As the effectiveness of such powerful and precise tools for cancer pharmacogenomic is emerging, reference datasets for their quality assessment and the validation of the underlying experimental pipelines are becoming increasingly necessary. Here, we provide a dataset, an R package, and metrics for the assessment of novel experimental pipelines upon the execution of a single calibration viability screen of the HT-29 human colon cancer cell line, employing a commercially available genome-wide library of single guide RNAs: the Human Improved Genome-wide Knockout CRISPR (Sanger) Library. This dataset contains results from screening the HT-29 in multiple batches with the Sanger library, and outcomes from several levels of quality control tests on the resulting data. Data and accompanying R package can be used as a toolkit for benchmarking newly established experimental pipelines for CRISPR-Cas9 recessive screens, via the generation of a final quality-control report.
“…The ability to discriminate prior known essential and non-essential genes based on their depletion LFC observed in a CRISPR-Cas9 recessive screen is widely used to assess the quality of that screen 3,5,7,9,10,23,26,27 .…”
Genome-wide recessive genetic screens using lentiviral CRISPR-guide RNA libraries are widely performed in mammalian cells to functionally characterise individual genes and for the discovery of new anti-cancer therapeutic targets. As the effectiveness of such powerful and precise tools for cancer pharmacogenomic is emerging, reference datasets for their quality assessment and the validation of the underlying experimental pipelines are becoming increasingly necessary. Here, we provide a dataset, an R package, and metrics for the assessment of novel experimental pipelines upon the execution of a single calibration viability screen of the HT-29 human colon cancer cell line, employing a commercially available genome-wide library of single guide RNAs: the Human Improved Genome-wide Knockout CRISPR (Sanger) Library. This dataset contains results from screening the HT-29 in multiple batches with the Sanger library, and outcomes from several levels of quality control tests on the resulting data. Data and accompanying R package can be used as a toolkit for benchmarking newly established experimental pipelines for CRISPR-Cas9 recessive screens, via the generation of a final quality-control report.
“…This approach is supported by the structure evident in the screen results, where very similar effects can be observed for multiple perturbations or different genes respond in synchrony across all of them. The concept of compressing perturbations has been used from model organism genetics (21) to cancer cell line characterization and relies on statistical reconstruction to balance experiment size against the chosen objective, for example, to explain variance in all outcomes, measure representatives in many categories, or even simply randomly choose the genes (15,104). Analogously, the outputs can be focused to obtain high-quality data from a key set of genes or to measure only an informative subset that allows the rest to be predicted (84,93).…”
Assigning functions to genes and learning how to control their expression are part of the foundation of cell biology and therapeutic development. An efficient and unbiased method to accomplish this is genetic screening, which historically required laborious clone generation and phenotyping and is still limited by scale today. The rapid technological progress on modulating gene function with CRISPR-Cas and measuring it in individual cells has now relaxed the major experimental constraints and enabled pooled screening with complex readouts from single cells. Here, we review the principles and practical considerations for pooled single-cell CRISPR screening. We discuss perturbation strategies, experimental model systems, matching the perturbation to the individual cells, reading out cell phenotypes, and data analysis. Our focus is on single-cell RNA sequencing and cell sorting–based readouts, including image-enabled cell sorting. We expect this transformative approach to fuel biomedical research for the next several decades. Expected final online publication date for the Annual Review of Genetics, Volume 57 is November 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
A major 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 widely-used computational method implemented as R/python package and in a dockerized version. CRISPRcleanR detects and corrects biased gene-independent responses to CRISPR-Cas9 targeting in an unsupervised fashion, and it accurately reduces false-positive signals, while maintaining sensitivity in identifying relevant genetic dependencies. Here we present CRISPRcleanRWebApp, a web-based application that enables access to CRISPRcleanR through an intuitive graphical web interface. CRISPRcleanRWebApp removes the complexity of low-level R/python-language user interactions, including a range of interactively explorable plots. In addition, it supports a wider range of CRISPR guide RNAs' libraries with respect to the original package. CRISPRcleanRWebApp is freely available and open to all users at: https://iorio-apps.fht.org/ccr.
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