ArticleNucleic acids research2018
OneD: increasing reproducibility of Hi-C samples with abnormal karyotypes.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs.Nature genetics · 2026Article
- Boosting the detection of enhancer-promoter loops via normalization methods for chromatin interaction data.Nature communications · 2026Article
- Uncovering the regulatory landscape of early human B cell lymphopoiesis and its implications in the pathogenesis of B-ALL.Science advances · 2025Article
- The Bioinformatic Applications of Hi-C and Linked Reads.Genomics, proteomics & bioinformatics · 2024Review
- Removing unwanted variation between samples in Hi-C experiments.Briefings in bioinformatics · 2024Article
- Tracing cancer evolution and heterogeneity using Hi-C.Nature communications · 2023Article
- 3D chromatin reprogramming primes human memory TScience immunology · 2023Article
- Detection and genomic analysis of BRAF fusions in Juvenile Pilocytic Astrocytoma through the combination and integration of multi-omic data.BMC cancer · 2022Article
- Coordinated changes in gene expression, H1 variant distribution and genome 3D conformation in response to H1 depletion.Nucleic acids research · 2022Article
- In vivo temporal resolution of acute promyelocytic leukemia progression reveals a role ofGenes & development · 2022Article
- Identification of chromatin loops from Hi-C interaction matrices by CTCF-CTCF topology classification.NAR genomics and bioinformatics · 2022Article
- Article
- Article
- Differential contribution to gene expression prediction of histone modifications at enhancers or promoters.PLoS computational biology · 2021Article
- CTCF chromatin residence time controls three-dimensional genome organization, gene expression and DNA methylation in pluripotent cells.Nature cell biology · 2021Article
- Chromosome compartments on the inactive X guide TAD formation independently of transcription during X-reactivation.Nature communications · 2021Article
- Genome-wide detection of enhancer-hijacking events from chromatin interaction data in rearranged genomes.Nature methods · 2021Article
- Orc4 spatiotemporally stabilizes centromeric chromatin.Genome research · 2021Article
- Resources and challenges for integrative analysis of nuclear architecture data.Current opinion in genetics & development · 2021Review
- Molecular and computational approaches to map regulatory elements in 3D chromatin structure.Epigenetics & chromatin · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The three-dimensional conformation of genomes is an essential component of their biological activity. The advent of the Hi-C technology enabled an unprecedented progress in our understanding of genome structures. However, Hi-C is subject to systematic biases that can compromise downstream analyses. Several strategies have been proposed to remove those biases, but the issue of abnormal karyotypes received little attention. Many experiments are performed in cancer cell lines, which typically harbor large-scale copy number variations that create visible defects on the raw Hi-C maps. The consequences of these widespread artifacts on the normalized maps are mostly unexplored. We observed that current normalization methods are not robust to the presence of large-scale copy number variations, potentially obscuring biological differences and enhancing batch effects. To address this issue, we developed an alternative approach designed to take into account chromosomal abnormalities. The method, called OneD, increases reproducibility among replicates of Hi-C samples with abnormal karyotype, outperforming previous methods significantly. On normal karyotypes, OneD fared equally well as state-of-the-art methods, making it a safe choice for Hi-C normalization. OneD is fast and scales well in terms of computing resources for resolutions up to 5 kb.
Indexed as
Identifiers
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.