Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

ACE: a probabilistic model for characterizing gene-level essentiality in CRISPR screens.

Genome biology - 23 Sept 2021

Hutton Elizabeth R, Vakoc Christopher R, Siepel Adam

Abstract excerpt

High-throughput CRISPR-Cas9 knockout screens are widely used to evaluate gene essentiality in cancer research. Here we introduce a probabilistic modeling framework, Analysis of CRISPR-based Essentiality (ACE), that accounts for multiple sources of variation in CRISPR-Cas9 screens and enables new statistical tests for essentiality. We show using simulations that ACE is effective at predicting both absolute and...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to CRISPR-Cas Systems
Share to Genes, Essential
Share to Genes, p53

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Genotype

Share to Models, Statistical

Share to Mutation

Share to Software

Source

Open in PubMed Open full text

Identifiers

PMID: 34556174
DOI: 10.1186/s13059-021-02491-z
PMCID: PMC8459512

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

ACE: a probabilistic model for characterizing gene-level essentiality in CRISPR screens.PMID 34556174Read ↗

Improved analysis of CRISPR fitness screens and reduced off-target effects with the BAGEL2 gene essentiality classifierSemantic proximity Read ↗

Measuring error rates in genomic perturbation screens: gold standards for human functional genomicsSemantic proximity Read ↗

Ranking of non-coding pathogenic variants and putative essential regions of the human genome.Semantic proximity Read ↗

Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells.Semantic proximity Read ↗

CEN-tools: an integrative platform to identify the contexts of essential genes.Semantic proximity Read ↗

In vivo and in vitro human gene essentiality estimations capture contrasting functional constraintsSemantic proximity Read ↗

OGEE v3: Online GEne Essentiality database with increased coverage of organisms and human cell lines.Semantic proximity Read ↗

Human gene essentiality.Semantic proximity Read ↗

Evaluation and Design of Genome-wide CRISPR/Cas9 Knockout ScreensSemantic proximity Read ↗

CEN-tools: An integrative platform to identify the ‘contexts’ of essential genesSemantic proximity Read ↗

Machine learning methods for predicting guide RNA effects in CRISPR epigenome editing experimentsSemantic proximity Read ↗

Assessing tissue-specific gene expression of essential genes from human and mouseSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.