ReviewGenomics, proteomics & bioinformatics2023
Computational Methods for Single-cell DNA Methylome Analysis.
Review in Genomics, proteomics & bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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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.
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.
Who cites it
16 citing papers in PubMed, 22 citations in OpenAlex.
- SMORE: joint dimension reduction and cell population discovery on single-cell methylome data.bioRxiv : the preprint server for biology · 2026Article
- Integrative Epigenomics: Bioinformatics Strategies for Multi-Omics Data Analysis in Health and Disease.Epigenomes · 2026Review
- Identification of SNPs Associated With mRNA Expression Differences of the Complement Receptor Type 1-Like Gene in Landrace Weaned Piglets.Veterinary medicine and science · 2026Article
- Ontology-aware DNA methylation classification with a curated atlas of human tissues and cell types.Cell reports methods · 2026Article
- Review
- KnowYourCG: Facilitating base-level sparse methylome interpretation.Science advances · 2025Article
- Single-cell DNA methylation analysis tool Amethyst resolves distinct non-CG methylation patterns in human astrocytes and oligodendrocytes.Communications biology · 2025Article
- A ternary-code DNA methylome atlas of mouse tissues.Genome biology · 2025Article
- Scalable screening of ternary-code DNA methylation dynamics associated with human traits.Cell genomics · 2025Article
- Imputing not available values in single-cell DNA methylation data using the median is straightforward and effective.Quantitative biology (Beijing, China) · 2025Article
- Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions.Briefings in bioinformatics · 2025Review
- Opportunities and challenges of single-cell and spatially resolved genomics methods for neuroscience discovery.Nature neuroscience · 2024Review
- The Role of Biophysical Factors in Organ Development: Insights from Current Organoid Models.Bioengineering (Basel, Switzerland) · 2024Review
- Low-input and single-cell methods for Infinium DNA methylation BeadChips.Nucleic acids research · 2024Article
- BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies.Nucleic acids research · 2024Article
- Single-Cell DNA Methylation Analysis in Cancer.Cancers · 2022Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Dissecting intercellular epigenetic differences is key to understanding tissue heterogeneity. Recent advances in single-cell DNA methylome profiling have presented opportunities to resolve this heterogeneity at the maximum resolution. While these advances enable us to explore frontiers of chromatin biology and better understand cell lineage relationships, they pose new challenges in data processing and interpretation. This review surveys the current state of computational tools developed for single-cell DNA methylome data analysis. We discuss critical components of single-cell DNA methylome data analysis, including data preprocessing, quality control, imputation, dimensionality reduction, cell clustering, supervised cell annotation, cell lineage reconstruction, gene activity scoring, and integration with transcriptome data. We also highlight unique aspects of single-cell DNA methylome data analysis and discuss how techniques common to other single-cell omics data analyses can be adapted to analyze DNA methylomes. Finally, we discuss existing challenges and opportunities for future development.
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What OpenQuestion holds
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.