ArticleCell reports methods2025
Differential performance of strategies for single-cell whole-genome amplification.
Article in Cell reports methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Origins and timing of somatic variants in the brain.Current opinion in genetics & development · 2026Review
- Nanopore Ultra-Long Sequencing for FSHD: From Molecular Diagnosis to Preimplantation Genetic Testing.Genes · 2026Review
- Article
- Single-cell deoxyribonucleic acid typing for forensic mixtures and trace evidence: Opportunities, validation requirements, and reporting limits.World journal of biological chemistry · 2026Review
- DIAG: A Framework for Evaluating Whole-Genome Amplification Quality in Single-Cell SNV Analysis.Biology · 2026Article
- Whole-Genome Amplification of Single Circulating Tumor Cells from Mice Xenografts.Methods in molecular biology (Clifton, N.J.) · 2026Article
- DelSIEVE: cell phylogeny modeling of single nucleotide variants and deletions from single-cell DNA sequencing data.Genome biology · 2025Article
- Article
- Flow Sorting, Whole Genome Amplification and Next-Generation Sequencing as Combined Tools to Study Heterogeneous Acute Lymphoblastic Leukemia.Diagnostics (Basel, Switzerland) · 2023Article
- Assessing the performance of methods for cell clustering from single-cell DNA sequencing data.PLoS computational biology · 2023Article
- DNA Polymerases for Whole Genome Amplification: Considerations and Future Directions.International journal of molecular sciences · 2023Review
- Microbial single-cell omics: the crux of the matter.Applied microbiology and biotechnology · 2020Review
- Methods for copy number aberration detection from single-cell DNA-sequencing data.Genome biology · 2020Review
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell genomics enables studying tissues and organisms at the highest resolution. However, since a cell contains a small amount of DNA, single-cell DNA sequencing (scDNA-seq) typically requires single-cell whole-genome amplification (scWGA). Unfortunately, scWGA methods introduce technical biases that complicate the interpretation of scDNA-seq data. We compared six scWGA methods, three MDA (multiple displacement amplification; GenomiPhi, REPLI-g, and TruePrime) and three non-MDA (Ampli1, MALBAC, and PicoPLEX), on 206 tumoral and 24 healthy human cells. scWGA methods performed differently depending on the parameter of interest. REPLI-g minimized regional amplification bias, while non-MDA methods showed a more uniform and reproducible amplification. Ampli1 exhibited the lowest allelic imbalance and dropout, the most accurate insertion or deletion (indel) and copy-number detection, and a low polymerase error rate. However, REPLI-g yielded higher DNA quantities, longer amplicons, and greater genome coverage. We offer a comprehensive guide for selecting a scWGA approach, outlining trade-offs that influence the interpretation of scDNA-seq data.
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