Evidence map›Paper›PMID 40976584›Full record

ArticleGenetics2026

gyōza: a Snakemake workflow for modular analysis of deep-mutational scanning data.

Romain Durand, Alicia Pageau, Christian R Landry

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

3 authors.

Romain DurandDépartement de Biochimie, de Microbiologie et de Bio-Informatique, Faculté des Sciences et de Génie, Université Laval, Québec (QC), G1V 0A6, Canada.ORCID 0000-0002-7681-4727
Alicia PageauDépartement de Biochimie, de Microbiologie et de Bio-Informatique, Faculté des Sciences et de Génie, Université Laval, Québec (QC), G1V 0A6, Canada.ORCID 0009-0004-9934-6390
Christian R LandryDépartement de Biochimie, de Microbiologie et de Bio-Informatique, Faculté des Sciences et de Génie, Université Laval, Québec (QC), G1V 0A6, Canada.ORCID 0000-0003-3028-6866

Funding

Canada Research Chair in Cellular Systems and Synthetic BiologyCIHR 387697Genome Canada and Genome Quebec 6569Natural Sciences and Engineering Research Council of Canada
6 · The paper itself

Abstract

Deep-mutational scanning (DMS) is a powerful technique that allows screening large libraries of mutants at high throughput. It has been used in many applications, including to estimate the fitness impact of all single mutants of entire proteins, to catalog drug resistance mutations, and even to predict protein structures. Here, we present gyōza, a Snakemake-based workflow to analyze DMS data. gyōza requires little programming knowledge and comes with comprehensive documentation to help the user go from raw sequencing data to functional impact scores. Complete with quality control and an automatically generated HTML report, this new pipeline should facilitate the analysis of time-series DMS experiments. gyōza is freely available on GitHub (https://github.com/durr1602/gyoza).

Indexed as

SoftwareDNA Mutational AnalysisMutationWorkflowdeep-mutational scanningDMSgyōzamutagenesismutational effectsselectionsequencingSnakemakeworkflow

Identifiers

PMID40976584
PMCPMC12774820

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.