The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient
Open accessPublished version of a preprint
Abstract
Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desired resolution. The measure consistently shows higher accuracy than existing approaches in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages. The proposed measure is straightforward to interpret and easy to compute, making it well-suited for providing standardized, interpretable, automatable, and scalable quality control. The freely available R package HiCRep implements our approach.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Notably, we found that samples were clustered by cell types, not individuals, and showed high correlation between the same cell types from different individuals (NeuN+ = 0.95–0.97; NeuN− = 0.86-0.91; Supplementary Fig. 3a), demonstrating the reproducibility across Hi–C libraries.”
From Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders (2021) · cites this paper as [19]
In the citing paper
“Clustering analysis by Hi-CRep49 showed that 5-AZA treated and DNMT TKD cells were more similar to each other than the DMSO treated cells (Fig. 6e).”
From Subtype-specific 3D genome alteration in acute myeloid leukaemia (2022) · cites this paper as [49]
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
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Hapeman, D. E., & Agresti, A. (1991) · Technometrics · doi:10.1080/00401706.1991.10484817 · Cited by 9,407
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
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898
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
Self-citationCapturing Chromosome Conformation
Dekker, J., Rippe, K., Dekker, M., & Kleckner, N. (2002) · Science · doi:10.1126/science.1067799 · Cited by 3,652
Chi-Square Tests with One Degree of Freedom; Extensions of the Mantel- Haenszel Procedure
Mantel, N. (1963) · Journal of the American Statistical Association · doi:10.1080/01621459.1963.10500879 · Cited by 2,899
HiC-Pro: an optimized and flexible pipeline for Hi-C data processing.
Servant, N., Varoquaux, N., Lajoie, B. R., Viara, E., Chen, C.-J., Vert, J.-P., Heard, E., Dekker, J., & Barillot, E. (2015) · Genome Biology · doi:10.1186/s13059-015-0831-x · Cited by 2,565 · cited 1×
“…replicates are available, it is a commonpracticetouseeitherPearsonorSpearmancorrelationco-efficients between the two Hi-C data matrices as a metric for data quality (Hu et al. 2012; Imakaev et al. 2012; Gorkin et al. 2014; Rao et al. 2014; Ay and Noble 2015; Dixon et al. 2015; Servant et al. 2015).”
On the probable error of a coefficient of correlation deduced from a small sample
Fisher, R. A. (1921) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 2,089
Chromatin architecture reorganization during stem cell differentiation
Dixon, J. R., Jung, I., Selvaraj, S., Shen, Y., Antosiewicz-Bourget, J. E., Lee, A. Y., Ye, Z., Kim, A., Rajagopal, N., Xie, W., et al. (2015) · Nature · doi:10.1038/nature14222 · Cited by 1,646
Single-cell Hi-C reveals cell-to-cell variability in chromosome structure
Nagano, T., Lubling, Y., Stevens, T. J., Schoenfelder, S., Yaffe, E., Dean, W., Laue, E. D., Tanay, A., & Fraser, P. (2013) · Nature · doi:10.1038/nature12593 · Cited by 1,589
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
Simonis, M., Klous, P., Splinter, E., Moshkin, Y., Willemsen, R., de Wit, E., van Steensel, B., & de Laat, W. (2006) · Nature Genetics · doi:10.1038/ng1896 · Cited by 1,386
Dostie, J., Richmond, T., Arnaout, R., Selzer, R. R., Lee, W. L., Honan, T., Rubio, E. D., Krumm, A., Lamb, J., Nusbaum, C., et al. (2006) · Genome Research · doi:10.1101/gr.5571506 · Cited by 1,237
A high-resolution map of the three-dimensional chromatin interactome in human cells
Jin, F., Li, Y., Dixon, J. R., Selvaraj, S., Ye, Z., Lee, A. Y., Yen, C.-A., Schmitt, A. D., Espinoza, C. A., & Ren, B. (2013) · Nature · doi:10.1038/nature12644 · Cited by 1,208
Chi-Square Tests with One Degree of Freedom; Extensions of the Mantel- Haenszel Procedure
Mantel, N. (1963) · Journal of the American Statistical Association · doi:10.2307/2282717 · Cited by 1,144
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
Exploring the three-dimensional organization of genomes: Interpreting chromatin interaction data
Dekker, J., Marti-Renom, M. A., & Mirny, L. A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3454 · Cited by 1,068
Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C
Mifsud, B., Tavares-Cadete, F., Young, A. N., Sugar, R., Schoenfelder, S., Ferreira, L., Wingett, S. W., Andrews, S., Grey, W., Ewels, P. A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3286 · Cited by 990
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
Epigenomic Analysis of Multilineage Differentiation of Human Embryonic Stem Cells
Xie, W., Schultz, M. D., Lister, R., Hou, Z., Rajagopal, N., Ray, P. R., Whitaker, J. W., Tian, S., Hawkins, R. D., Leung, D., et al. (2013) · Cell · doi:10.1016/j.cell.2013.04.022 · Cited by 739
Yaffe, E., & Tanay, A. (2011) · Nature Genetics · doi:10.1038/ng.947 · Cited by 614
ENCODE data at the ENCODE portal
Sloan, C. A., Chan, E. T., Davidson, J. M., Malladi, V. S., Strattan, J. S., Hitz, B. C., Gabdank, I., Narayanan, A. K., Ho, M., Lee, B. T., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1160 · Cited by 549
Statistical confidence estimation for Hi-C data reveals regulatory chromatin contactsPreprint
Ay, F., Bailey, T. L., & Noble, W. S. (2014) · Genome Research · doi:10.1101/gr.160374.113 · Cited by 479
Self-citationHughes, J. R., Roberts, N., McGowan, S., Hay, D., Giannoulatou, E., Lynch, M., De Gobbi, M., Taylor, S., Gibbons, R., & Higgs, D. R. (2014) · Nature Genetics · doi:10.1038/ng.2871 · Cited by 461 · cited 3×
“A progression of high-throughput methods based on chromatin conformation capture (3C) (Dekker 2002) has emerged, including 4C (Simonis et al. 2006), 5C (Dostie et al. 2006), Hi-C (Lieberman-Aiden et al. 2009), ChIA-PET (Li et al. 2010), Capture Hi-C (Hughes et al. 2014; Mifsud et al.2015), andHiChIP(Mumbach et al.2016…”
The Role of Chromosome Domains in Shaping the Functional Genome
Sexton, T., & Cavalli, G. (2015) · Cell · doi:10.1016/j.cell.2015.02.040 · Cited by 427
The Hitchhiker’s guide to Hi-C analysis: Practical guidelines
Lajoie, B. R., Dekker, J., & Kaplan, N. (2014) · Methods · doi:10.1016/j.ymeth.2014.10.031 · Cited by 394
The 3D genome in transcriptional regulation and pluripotency
Gorkin, D. U., Leung, D., & Ren, B. (2014) · Cell Stem Cell · doi:10.1016/j.stem.2014.05.017 · Cited by 391
The Spatial Organization of the Human Genome
Bickmore, W. A. (2013) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-091212-153515 · Cited by 391
ChIA-PET tool for comprehensive chromatin interaction analysis with paired-end tag sequencing
Li, G., Fullwood, M. J., Han, X., Mulawadi, F. H., Velkov, S., Vega, V. B., Ariyaratne, P. N., Mohamed, Y. B., Ooi, H.-S., Tennakoon, C., et al. (2010) · Genome biology · doi:10.1186/gb-2010-11-2-r22 · Cited by 323
Whole-genome haplotype reconstruction using proximity-ligation and shotgun sequencing
Selvaraj, S., Dixon, J. R., Bansal, V., & Ren, B. (2013) · Nature Biotechnology · doi:10.1038/nbt.2728 · Cited by 294
HiCNorm: removing biases in Hi-C data via Poisson regression
Hu, M., Deng, K., Selvaraj, S., Qin, Z., Ren, B., & Liu, J. S. (2012) · Bioinform. · doi:10.1093/bioinformatics/bts570 · Cited by 250
Integrative analysis of haplotype-resolved epigenomes across human tissues
Leung, D., Jung, I., Rajagopal, N., Schmitt, A. D., Selvaraj, S., Lee, A. Y., Yen, C., Lin, S., Lin, Y., Qiu, Y., et al. (2015) · Nature · doi:10.1038/nature14217 · Cited by 228
Self-citationHigher-order Genome Organization in Human DiseasePreprint
Misteli, T. (2010) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a000794 · Cited by 223
Normalization of a chromosomal contact map
Cournac, A., Marie-Nelly, H., Marbouty, M., Koszul, R., & Mozziconacci, J. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-436 · Cited by 217
Computer and Machine Vision: Theory, Algorithms, Practicalities
Davies, E. R. (2012) · Cited by 208
Higher-order chromatin structure: bridging physics and biology
Fudenberg, G., & Mirny, L. A. (2012) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2012.01.006 · Cited by 177
Analysis methods for studying the 3D architecture of the genome
Ay, F., & Noble, W. S. (2015) · Genome biology · doi:10.1186/s13059-015-0745-7 · Cited by 175
Self-citationA view of the chromatin landscape
Rapkin, L. M., Anchel, D., Li, R., & Bazett‐Jones, D. P. (2011) · Micron · doi:10.1016/j.micron.2011.11.007 · Cited by 43
Explaining community-level variance in group randomized trials
Feng, Z., Diehr, P. H., Yasui, Y., Evans, B. A., Beresford, S. A. A., & Koepsell, T. D. (1999) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19990315)18:5 · Cited by 35
Flagged first, then by citations
Research works printed but not linked: 1
- Casella G , Berger GL . 2002. Statistical inference, 2nd ed. Duxbury Press, Pacific Grove, CA.
Cited by
Sorted by citations
Resolving the 3D Landscape of Transcription-Linked Mammalian Chromatin Folding
Hsieh, T.-H. S., Cattoglio, C., Slobodyanyuk, E., Hansen, A. S., Rando, O. J., Tjian, R., & Darzacq, X. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.03.002 · Cited by 661
Loss of epigenetic information as a cause of mammalian aging
Yang, J.-H., Hayano, M., Griffin, P. T., Amorim, J. A., Bonkowski, M. S., Apostolides, J. K., Salfati, E. L., Blanchette, M., Munding, E. M., Bhakta, M., et al. (2023) · Cell · doi:10.1016/j.cell.2022.12.027 · Cited by 643
The structural basis for cohesin–CTCF-anchored loops
Li, Y., Haarhuis, J. H. I., Sedeño Cacciatore, Á., Oldenkamp, R., van Ruiten, M. S., Willems, L., Teunissen, H., Muir, K. W., de Wit, E., Rowland, B. D., et al. (2020) · Nature · doi:10.1038/s41586-019-1910-z · Cited by 459
Simultaneous profiling of 3D genome structure and DNA methylation in single human cells
Lee, D.-S., Luo, C., Zhou, J., Chandran, S., Rivkin, A., Bartlett, A., Nery, J. R., Fitzpatrick, C., O’Connor, C., Dixon, J. R., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0547-z · Cited by 340
Promoter-proximal CTCF binding promotes distal enhancer-dependent gene activation
Kubo, N., Ishii, H., Xiong, X., Bianco, S., Meitinger, F., Hu, R., Hocker, J. D., Conte, M., Gorkin, D., Yu, M., et al. (2021) · Nature Structural & Molecular Biology · doi:10.1038/s41594-020-00539-5 · Cited by 289
Metadata
- Authors
- Yang, T., Zhang, F., Yardımcı, G. G., Song, F., Hardison, R. C., Noble, W. S., Yue, F., & Li, Q.
- Affiliations
- Pennsylvania State University (US)
- University of Washington (US)
- ORCID
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2017-08-30
- Volume
- 27
- Issue
- 11
- Pages
- 1939-1949
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- PMC
- PMC5668950
- OpenAlex
- W2952940726
- Cited by
- 533
- References
- 41
- Citations by year
- 2026: 48 · 2025: 68 · 2024: 98 · 2023: 69 · 2022: 57 · 2021: 73 · 2020: 60 · 2019: 38 · 2018: 18 · 2017: 4
- Type
- posted content
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- Genome Research (publishedVersion, public-domain)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institutes of Health (T32 GM102057)
- Huck Graduate Research Innovation
- NIH (R01GM109453, U01CA200060, R24DK106766, U54HG006998, U41HG007000)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Keywords
- Hi-C, domain structure, distance dependence, cell lineage
- MeSH terms
- Cell Line, Humans, Software, Reproducibility of Results, Sequence Analysis, RNA, Cell Lineage, Computational Biology, Chromatin Immunoprecipitation, High-Throughput Nucleotide Sequencing
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
