Evidence map›Paper›PMID 41542642›Full record

ArticlebioRxiv : the preprint server for biology2026

Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens.

Maximilian Billmann, Michael Costanzo, Mahfuzur Rahman, Katherine Chan, Amy Hin Yan Tong, Henry N Ward, Arshia Z Hassan, Xiang Zhang, Kevin R Brown, Thomas Rohde and 12 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Maximilian BillmannDepartment of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-6556-9594
Michael CostanzoDonnelly Centre, University of Toronto, Toronto ON, Canada.ORCID 0000-0002-7906-2604
Mahfuzur RahmanDepartment of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-9226-3988
Katherine ChanProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Amy Hin Yan TongDonnelly Centre, University of Toronto, Toronto ON, Canada.
Henry N WardDepartment of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-9869-9790
Arshia Z HassanDepartment of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-5773-9186
Xiang ZhangDepartment of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.
Kevin R BrownProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.ORCID 0000-0002-5514-2538
Thomas RohdeInstitute of Human Genetics, School of Medicine and University Hospital Bonn, University of Bonn, Bonn, Germany.ORCID 0009-0004-5159-4635
Angela H ShawInstitute of Human Genetics, School of Medicine and University Hospital Bonn, University of Bonn, Bonn, Germany.ORCID 0000-0002-1288-6529
Catherine RossDonnelly Centre, University of Toronto, Toronto ON, Canada.
Jolanda van LeeuwenDonnelly Centre, University of Toronto, Toronto ON, Canada.ORCID 0000-0003-3991-518X
Michael AreggerDonnelly Centre, University of Toronto, Toronto ON, Canada.ORCID 0000-0001-6443-9870
Keith LawsonDonnelly Centre, University of Toronto, Toronto ON, Canada.
Barbara MairDonnelly Centre, University of Toronto, Toronto ON, Canada.ORCID 0000-0001-6982-2529
Patricia MeroProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada.
Matej UsajDonnelly Centre, University of Toronto, Toronto ON, Canada.
Brenda AndrewsDonnelly Centre, University of Toronto, Toronto ON, Canada.ORCID 0000-0001-6427-6493
Charles BooneDonnelly Centre, University of Toronto, Toronto ON, Canada.ORCID 0000-0002-3542-6760
Jason MoffatDonnelly Centre, University of Toronto, Toronto ON, Canada.ORCID 0000-0002-5663-8586
Chad L MyersDepartment of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-1026-5972

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic interaction (GI) networks in model organisms have revealed how combinations of genome variants can impact phenotypes. To advance efforts toward a reference human GI network, we developed the quantitative Genetic Interaction (qGI) score, a method for precise GI measurement from genome-wide CRISPR-Cas9 screens in different query mutants constructed in a single human cell line. We found surprising prevalent systematic variation unrelated to GIs in CRISPR screen data, including both genomically linked effects and functionally coherent covariation. Leveraging ~40 control screens in wild-type cells and half a billion differential fitness effect measurements, we developed a pipeline for CRISPR screen data processing and normalization to correct these artifacts and measure accurate, quantitative GIs. We also comprehensively characterized GI reproducibility by characterizing 4 - 5 biological replicates for ~125,000 unique gene pairs. The qGI framework enables systematic identification of human GIs and provides broadly applicable strategies for analyzing context-specific CRISPR screen data.

Identifiers

PMID41542642
PMCPMC12803112

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.