ArticleNature communications2015
Calibrating genomic and allelic coverage bias in single-cell sequencing.
Article in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
- Phylogenetic and phylodynamic approaches to understanding the evolution of non-small cell lung cancer using single-cell sequencing.Oncogene · 2026Article
- Somatic mosaicism in the brain: linking development, ageing and neurodegeneration.Nature reviews. Neurology · 2026Review
- Review
- CoSAG-nf: a scalable nextflow pipeline for co-assembly, optimization, and interactive visualization of high-throughput single-cell genomes.Bioinformatics (Oxford, England) · 2026Article
- Preimplantation genetic testing for polygenic diseases: A novel paradigm in embryo selection.Biochemistry and biophysics reports · 2026Review
- Advances in single-cell DNA sequencing enable insights into human somatic mosaicism.Nature reviews. Genetics · 2025Review
- Metagenomic approaches for studying ubiquitous yet diverse nucleoid associated proteins in microbial communities: challenges and advances.World journal of microbiology & biotechnology · 2025Review
- Differential performance of strategies for single-cell whole-genome amplification.Cell reports methods · 2025Article
- High-resolution detection of copy number alterations in single cells with HiScanner.bioRxiv : the preprint server for biology · 2025Article
- Long-read whole-genome sequencing-based concurrent haplotyping and aneuploidy profiling of single cells.Nucleic acids research · 2025Article
- Single-cell somatic copy number variants in brain using different amplification methods and reference genomes.Communications biology · 2024Article
- De novo detection of somatic mutations in high-throughput single-cell profiling data sets.Nature biotechnology · 2024Article
- A medium-density genotyping platform for cultivated strawberry using DArTag technology.The plant genome · 2023Article
- Single-cell somatic copy number variants in brain using different amplification methods and reference genomes.bioRxiv : the preprint server for biology · 2023Article
- Identification of a novel family B DNA polymerase from Enterococcus phage IME199 and its overproduction in Escherichia coli BL21(DE3).Microbial cell factories · 2023Article
- Single-cell whole-genome sequencing, haplotype analysis in prenatal diagnosis of monogenic diseases.Life science alliance · 2023Article
- Back to Basics: A Simplified Improvement to Multiple Displacement Amplification for Microbial Single-Cell Genomics.International journal of molecular sciences · 2023Article
- Single-cell genome sequencing of human neurons identifies somatic point mutation and indel enrichment in regulatory elements.Nature genetics · 2022Article
- Comprehensive Evaluation of RNA and DNA Viromic Methods Based on Species Richness and Abundance Analyses Using Marmot Rectal Samples.mSystems · 2022Article
- Droplet-microfluidics-assisted sequencing of HIV proviruses and their integration sites in cells from people on antiretroviral therapy.Nature biomedical engineering · 2022Article
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9 authors.
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Abstract
Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1-10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples.
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