ArticlebioRxiv : the preprint server for biology2026
simCRISPR: Modeling Experimental Complexity in Pooled CRISPR Screens.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Pooled CRISPR screens are widely used to investigate gene function and uncover genetic interactions. However, benchmarking computational methods for detecting gene-by-environment (GxE) interactions remains difficult because ground truth is rarely available and existing simulation tools are not designed for GxE screening contexts. To address this, we developed simCRISPR, a flexible simulation framework for generating pooled CRISPR screen data under complex experimental designs. Using simulated datasets informed by empirical CRISPR screen designs, we evaluated commonly used analysis methods, comparing normalization strategies based on safe-harbor versus non-targeting sgRNAs and assessing empirical log
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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 Socratic graph.