ArticleScience advances2025
KnowYourCG: Facilitating base-level sparse methylome interpretation.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
4 citing papers in PubMed.
- CpG Atlas: A centralized multi-layer database and AI interface for DNA methylation research.bioRxiv : the preprint server for biology · 2026Article
- Low Depth Epigenetic Mapping of Maturation Versus Retrodifferentiation in HepaRG Cells.Epigenomes · 2026Article
- Continuous DNA methylation deconvolution-based surrogate for B-cell differentiation state in chronic lymphocytic leukemia.Communications medicine · 2026Article
- DNA Methylation-Based Risk Stratification and Classification of Pediatric Thyroid Carcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Decoding DNA methylomes for biological insights is critical in epigenetics research. We present KnowYourCG (KYCG), a data interpretation framework designed for functional DNA methylation analysis. Unlike existing tools that target genes or genomic intervals, KYCG features direct base-level screenings of diverse biological and technical influences, including sequence motifs, transcription factor binding, histone modifications, replication timing, cell-type-specific methylation, and trait associations. Through implementing efficient infrastructure that rapidly screens and investigates thousands of knowledgebases, KYCG addresses the challenges of data sparsity in various methylation datasets, including low-pass or single-cell DNA methylomes, 5-hydroxymethylation (5hmC) profiles, spatial DNA methylation maps, and array-based datasets for epigenome-wide association studies. Applying KYCG to these datasets provides valuable insights into cell differentiation, cancer origins, epigenome-trait associations, and technical issues such as array artifacts, single-cell batch effects, and Nanopore 5hmC detection accuracy. Our tool simplifies large-scale methylation analysis and integrates seamlessly with standard assay technologies.
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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.