The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts
Open accessAbstract
Our current understanding of how DNA is packed in the nucleus is most accurate at the fine scale of individual nucleosomes and at the large scale of chromosome territories. However, accurate modeling of DNA architecture at the intermediate scale of ∼50 kb–10 Mb is crucial for identifying functional interactions among regulatory elements and their target promoters. We describe a method,Fit-Hi-C, that assigns statistical confidence estimates to mid-range intra-chromosomal contacts by jointly modeling the random polymer looping effect and previously observed technical biases in Hi-C data sets. We demonstrate that our proposed approach computes accurate empirical null models of contact probability without any distribution assumption, corrects for binning artifacts, and provides improved statistical power relative to a previously described method. High-confidence contacts identified by Fit-Hi-C preferentially link expressed gene promoters to active enhancers identified by chromatin signatures in human embryonic stem cells (ESCs), capture 77% of RNA polymerase II-mediated enhancer-promoter interactions identified using ChIA-PET in mouse ESCs, and confirm previously validated, cell line-specific interactions in mouse cortex cells. We observe that insulators and heterochromatin regions are hubs for high-confidence contacts, while promoters and strong enhancers are involved in fewer contacts. We also observe that binding peaks of master pluripotency factors such as NANOG and POU5F1 are highly enriched in high-confidence contacts for human ESCs. Furthermore, we show that pairs of loci linked by high-confidence contacts exhibit similar replication timing in human and mouse ESCs and preferentially lie within the boundaries of topological domains for human and mouse cell lines.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829
Spatial partitioning of the regulatory landscape of the X-inactivation centre
Nora, E. P., Lajoie, B. R., Schulz, E. G., Giorgetti, L., Okamoto, I., Servant, N., Piolot, T., van Berkum, N. L., Meisig, J., Sedat, J., et al. (2012) · Nature · doi:10.1038/nature11049 · Cited by 2,895
A unique chromatin signature uncovers early developmental enhancers in humans
Rada-Iglesias, A., Bajpai, R., Swigut, T., Brugmann, S. A., Flynn, R. A., & Wysocka, J. (2011) · Nature · doi:10.1038/nature09692 · Cited by 2,233
The long-range interaction landscape of gene promoters
Sanyal, A., Lajoie, B. R., Jain, G., & Dekker, J. (2012) · Nature · doi:10.1038/nature11279 · Cited by 1,489
Iterative correction of Hi-C data reveals hallmarks of chromosome organization
Imakaev, M., Fudenberg, G., McCord, R. P., Naumova, N., Goloborodko, A., Lajoie, B. R., Dekker, J., & Mirny, L. A. (2012) · Nature Methods · doi:10.1038/nmeth.2148 · Cited by 1,423
A map of the cis-regulatory sequences in the mouse genome
Shen, Y., Yue, F., McCleary, D. F., Ye, Z., Edsall, L., Kuan, S., Wagner, U., Dixon, J., Lee, L., Lobanenkov, V. V., et al. (2012) · Nature · doi:10.1038/nature11243 · Cited by 1,361 · cited 12×
“Both of the genes transcribed from these promoters ( Gucy1a3 , Gucy1b3 ), as well as a third gene that is 212 kb downstream from the Gucy1a3 promoter ( Map9 ), exhibit cortex-specific expression (Shen et al. 2012).”
BackgroundMethodResultInfluentialLooping and Interaction between Hypersensitive Sites in the Active β-globin Locus
Tolhuis, B., Palstra, R.-J., Splinter, E., Grosveld, F., & de Laat, W. (2002) · Molecular Cell · doi:10.1016/s1097-2765(02)00781-5 · Cited by 1,344
Cited by
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212
HiChIP: efficient and sensitive analysis of protein-directed genome architecture
Mumbach, M. R., Rubin, A. J., Flynn, R. A., Dai, C., Khavari, P. A., Greenleaf, W. J., & Chang, H. Y. (2016) · Nature Methods · doi:10.1038/nmeth.3999 · Cited by 1,139
Satpathy, A. T., Granja, J. M., Yost, K. E., Qi, Y., Meschi, F., McDermott, G. P., Olsen, B. N., Mumbach, M. R., Pierce, S. E., Corces, M. R., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0206-z · Cited by 980
A compendium of chromatin contact maps reveals spatially active regions in the human genome
Schmitt, A. D., Hu, M., Jung, I., Xu, Z., Qiu, Y., Tan, C. L., Li, Y., Lin, S., Lin, Y., Barr, C. L., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.10.061 · Cited by 866
HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient
Yang, T., Zhang, F., Yardımcı, G. G., Song, F., Hardison, R. C., Noble, W. S., Yue, F., & Li, Q. (2017) · Genome Research · doi:10.1101/gr.220640.117 · Cited by 533
Self-citation
Metadata
- Authors
- Ay, F., Bailey, T. L., & Noble, W. S.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2014-02-05
- Volume
- 24
- Issue
- 6
- Pages
- 999-1011
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2142270559
- Cited by
- 491
- References
- 8
- Type
- posted content
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts. https://app.cochat.ai/papers/10.1101/gr.160374.113
- The paper
- Ay, F., Bailey, T. L., & Noble, W. S. (2014). Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts. Genome Research. https://doi.org/10.1101/gr.160374.113
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.