ArticleBiostatistics (Oxford, England)2024
Exponential family measurement error models for single-cell CRISPR screens.
Article in Biostatistics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Canon enables causal inference of downstream genes in single-cell CRISPR studies via instrumental variable analysis.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Segmentally Duplicated Regulatory Elements Undergo Human-Specific Rewiring.Molecular biology and evolution · 2026Article
- Genome-scale mapping of variant, enhancer and gene function in primary human CD4+ T cells.bioRxiv : the preprint server for biology · 2026Article
- Segmentally duplicated regulatory elements undergo human-specific rewiring.bioRxiv : the preprint server for biology · 2025Article
- Large-scale discovery of neural enhancers for cis-regulation therapies.bioRxiv : the preprint server for biology · 2025Article
- Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements.Nature communications · 2024Article
- Guide assignment in single-cell CRISPR screens using crispat.Bioinformatics (Oxford, England) · 2024Article
- Next-generation forward genetic screens: uniting high-throughput perturbations with single-cell analysis.Trends in genetics : TIG · 2024Review
- Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
CRISPR genome engineering and single-cell RNA sequencing have accelerated biological discovery. Single-cell CRISPR screens unite these two technologies, linking genetic perturbations in individual cells to changes in gene expression and illuminating regulatory networks underlying diseases. Despite their promise, single-cell CRISPR screens present considerable statistical challenges. We demonstrate through theoretical and real data analyses that a standard method for estimation and inference in single-cell CRISPR screens-"thresholded regression"-exhibits attenuation bias and a bias-variance tradeoff as a function of an intrinsic, challenging-to-select tuning parameter. To overcome these difficulties, we introduce GLM-EIV ("GLM-based errors-in-variables"), a new method for single-cell CRISPR screen analysis. GLM-EIV extends the classical errors-in-variables model to responses and noisy predictors that are exponential family-distributed and potentially impacted by the same set of confounding variables. We develop a computational infrastructure to deploy GLM-EIV across hundreds of processors on clouds (e.g. Microsoft Azure) and high-performance clusters. Leveraging this infrastructure, we apply GLM-EIV to analyze two recent, large-scale, single-cell CRISPR screen datasets, yielding several new insights.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.