ArticleGenome biology2020
DiMSum: an error model and pipeline for analyzing deep mutational scanning data and diagnosing common experimental pathologies.
Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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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.
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Who cites it
65 citing papers in PubMed.
- Scanning the horizon: deep mutational scanning approaches in virology.Journal of virology · 2026Review
- Dual functional genomics reveals a broad and convergent landscape of asciminib resistance in BCR::ABL1.Genome medicine · 2026Article
- Regulatory landscape of widespread stop codon readthrough inbioRxiv : the preprint server for biology · 2026Article
- CountESS: a flexible, graphical pipeline tool for deep mutational scanning analysis.bioRxiv : the preprint server for biology · 2026Article
- Seven complete comparative maps of allosteric mutations in a protein family.Nature communications · 2026Article
- The genetic architecture of an allosteric hormone receptor.Nature communications · 2026Article
- Massively parallel quantification of mutational impact on IAPP amyloid formation.Nature communications · 2026Article
- Creating an atlas of variant effects to resolve variants of uncertain significance and guide cardiovascular medicine.Nature reviews. Cardiology · 2026Review
- Allosteric and energetic remodeling of a PDZ domain by protein domain extensions.Nature communications · 2026Article
- The allosteric landscape of the Src kinase.Science advances · 2026Article
- Article
- A splice-switching antisense oligonucleotide approach for pediatric genetic epilepsies.bioRxiv : the preprint server for biology · 2025Article
- Deep Mutational Scanning in Immunology: Techniques and Applications.Pathogens (Basel, Switzerland) · 2025Review
- Variant scoring tools for deep mutational scanning.Molecular systems biology · 2025Review
- Distinguishing direct interactions from global epistasis using rank statistics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Divergent resistance pathways amongst SARS-CoV-2 PLpro inhibitors highlight the need for scaffold diversity.PLoS pathogens · 2025Article
- Deep indel mutagenesis reveals the regulatory and modulatory architecture of alternative exon splicing.Nature communications · 2025Article
- Cosmos: A Position-Resolution Causal Model for Direct and Indirect Effects in Protein Functions.bioRxiv : the preprint server for biology · 2025Article
- Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.Science advances · 2025Article
- Massive mutagenesis reveals an incomplete amyloid motif in Bri2 that turns amyloidogenic upon C-terminal extension.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Deep mutational scanning (DMS) enables multiplexed measurement of the effects of thousands of variants of proteins, RNAs, and regulatory elements. Here, we present a customizable pipeline, DiMSum, that represents an end-to-end solution for obtaining variant fitness and error estimates from raw sequencing data. A key innovation of DiMSum is the use of an interpretable error model that captures the main sources of variability arising in DMS workflows, outperforming previous methods. DiMSum is available as an R/Bioconda package and provides summary reports to help researchers diagnose common DMS pathologies and take remedial steps in their analyses.
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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 OpenQuestion graph.