ArticleGenome biology2024
sciMET-cap: high-throughput single-cell methylation analysis with a reduced sequencing burden.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Early postnatal DNA methylation dynamics define neuronal subtypes and are disrupted by MECP2 loss.bioRxiv : the preprint server for biology · 2026Article
- Deconvolution of DNA methylation data reveals cell type-specific epigenomic signatures in endometriosis and eutopic endometrium.Molecular human reproduction · 2026Article
- Review
- Targeted long-read methylation analysis using hybridization capture suitable for clinical specimens.Cell reports methods · 2025Article
- Single-cell DNA methylation analysis tool Amethyst resolves distinct non-CG methylation patterns in human astrocytes and oligodendrocytes.Communications biology · 2025Article
- Imputing not available values in single-cell DNA methylation data using the median is straightforward and effective.Quantitative biology (Beijing, China) · 2025Article
- Atlas-scale single-cell DNA methylation profiling with sciMETv3.Cell genomics · 2025Article
- sciMET-cap: high-throughput single-cell methylation analysis with a reduced sequencing burden.Genome biology · 2024Article
- The emerging field of opportunities for single-cell DNA methylation studies in hematology and beyond.Frontiers in molecular biosciences · 2023Article
Corrections and comments
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Authors and funding
6 authors.
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Abstract
DNA methylation is a key component of the mammalian epigenome, playing a regulatory role in development, disease, and other processes. Robust, high-throughput single-cell DNA methylation assays are now possible (sciMET); however, the genome-wide nature of DNA methylation results in a high sequencing burden per cell. Here, we leverage target enrichment with sciMET to capture sufficient information per cell for cell type assignment using substantially fewer sequence reads (sciMET-cap). Accumulated off-target coverage enables genome-wide differentially methylated region (DMR) calling for clusters with as few as 115 cells. We characterize sciMET-cap on human PBMCs and brain (middle frontal gyrus).
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Registered trials
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