HiC-Pro: an optimized and flexible pipeline for Hi-C data processing.
Open accessAbstract
HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro .
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
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?
SNPsplit has the unique capability to work with several different data types.
“While a similar allele-specific functionality has been integrated into specialised applications, e.g. HiC-Pro 10, the unique capability to work with several different data types renders SNPsplit an ideal choice for correlation studies using allele-specific sequencing reads.”
From SNPsplit: Allele-specific splitting of alignments between genomes with known SNP genotypes (2016) · cites this paper as [10]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
References 24 · Cited by 2,565
Research works printed but not linked: 18
- [1]de Wit E de Laat W A decade of 3C technologies: insights into nuclear organization Genes Dev. 2012 26 11 24 10.1101/gad.179804.111 22215806 PMC3258961 · DOI
- [2]Barutcu AR, Fritz AJ, Sayyed KZ, van Wijnen AJ, Lian JB, Stein JL, et al. C-ing the genome: A compendium of chromosome conformation capture methods to study higher-order chromatin organization. J Cell Physiol. 2015;1097–4652. doi:10.1002/jcp.25062. PMC4586368 26059817 · DOI
- [3]Lieberman-Aiden E van Berkum NL Williams L Imakaev M Ragoczy T Telling A Comprehensive mapping of long-range interactions reveals folding principles of the human genome Science 2009 326 5950 289 293 10.1126/science.1181369 19815776 PMC2858594 · DOI · Paper page
- [4]Ma W Ay F Lee C Gulsoy G Deng X Cook S Fine-scale chromatin interaction maps reveal the cis-regulatory landscape of lincRNA genes in human cells Nat Methods. 2015 12 71 78 10.1038/nmeth.3205 25437436 PMC4281301 · DOI
- [7]Rao SSP Huntley MH Durand NC Bochkov SID Robinson JT Sanborn AL A 3d map of the human genome at kilobase resolution reveals principles of chromatin looping Cell 2014 159 7 1665 1680 10.1016/j.cell.2014.11.021 25497547 PMC5635824 · DOI · Paper page
- [8]Jin F Li Y Dixon JR Selvaraj S Ye Z Lee Y A high-resolution map of the three-dimensional chromatin interactome in human cells Nature 2013 503 7475 290 294 24141950 PMC3838900
- [9]Lajoie BR Dekker J Kaplan N The hitchhiker’s guide to hi-c analysis: Practical guidelines Methods. 2015 72 65 75 10.1016/j.ymeth.2014.10.031 25448293 PMC4347522 · DOI
- [10]Heinz S Benner C Spann N Bertolino E Lin YC Lasio P Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities Mol Cell 2010 38 4 576 589 10.1016/j.molcel.2010.05.004 20513432 PMC2898526 · DOI · Paper page
- [12]Castellano G, Le Dily F, Hermoso Pulido A, Beato M, Roma G. Hi-Cpipe: a pipeline for high-throughput chromosome capture. bioRxiv 2015. Cold Spring Harbor Labs Journals. doi:10.1101/020636. · DOI
- [13]Schmid Marc W Schmid MW Grob S Grossniklaus U HiCdat: a fast and easy-to-use Hi-C data analysis tool BMC Bioinformatics. 2015 16 277 10.1186/s12859-015-0678-x 26334796 PMC4559209 · DOI
- [18]Yaffe E Tanay A Probabilistic modelling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture Nat Genet 2011 43 11 1059 1065 10.1038/ng.947 22001755 · DOI
- [19]Hu M Deng K Selvaraj S Qin Z Ren B Liu J HiCNorm: removing biases in Hi-C data via poisson regression Bioinformatics 2012 28 23 3131 3133 10.1093/bioinformatics/bts570 23023982 PMC3509491 · DOI
- [20]Li W Gong K Li Q Alber Fand Zhou XJ Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale hi-c data Bioinformatics 2015 31 6 960 962 10.1093/bioinformatics/btu747 25391400 PMC4380031 · DOI
- [21]Minajigi A, Froberg JE, Wei C, Sunwoo H, Kesner B, Colognori D, et al. A comprehensive Xist interactome reveals cohesin repulsion and an RNA-directed chromosome conformation. Science. 2015;349(6245):aab2276. doi:10.1126/science.aab2276. PMC4845908 26089354 · DOI
- [22]Deng X Ma W Ramani V Hill A Yang F Ay F Bipartite structure of the inactive mouse X chromosome Genome Biol. 2015 16 152 10.1186/s13059-015-0728-8 26248554 PMC4539712 · DOI
- [23]Selvaraj S Dixon JR Bansal V Ren B Whole-genome haplotype reconstruction using proximity-ligation ans shotgun sequencing Nat Biotechnol 2013 31 12 1111 1118 10.1038/nbt.2728 24185094 PMC4180835 · DOI
- [27]Cournac A Marie-Nelly H Marbouty M Koszul R Mozziconacci J Normalization of a chromosomal contact map BMC Genomics. 2012 13 436 10.1186/1471-2164-13-436 22935139 PMC3534615 · DOI
- [28]Servant N Lajoie BR Nora EP Giorgetti L Chen CJ Heard E HiTC: Exploration of high-throughput ‘C’ experiments Bioinformatics 2012 28 21 2843 2844 10.1093/bioinformatics/bts521 22923296 PMC3476334 · DOI
- Authors
- Servant, N., Varoquaux, N., Lajoie, B. R., Viara, E., Chen, C.-J., Vert, J.-P., Heard, E., Dekker, J., & Barillot, E.
- Affiliations
- Inserm (FR)
- University of Massachusetts Chan Medical School (US)
- SYSTRA (France) (FR)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Servant, Nicolas
- ORCID
- Venue
- Genome Biology
- Published
- 2015-12
- Volume
- 16
- Issue
- 1
- Pages
- 259-259
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC4665391
- OpenAlex
- W2185693210
- Cited by
- 2,565
- References
- 24
- Citations by year
- 2026: 237 · 2025: 347 · 2024: 401 · 2023: 347 · 2022: 334 · 2021: 359 · 2020: 241 · 2019: 156 · 2018: 83 · 2017: 41 · 2016: 11 · 2015: 3
- FWCI
- 19.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- The Journal of the American Medical Association (JAMA) Network (American Medical Association) (submittedVersion, cc-by)
- HAL (submittedVersion)
- Funders
- Agence Nationale de la Recherche (ANR-10-INBS-09, ANR-11-BINF-0001, Paris Alliance of Cancer Research Institutes)
- European Research Coucil (SMAC-ERC-280032)
- ERC Advanced Investigator award (ERC- 250367)
- European Commission (HEALTH-F5-2012-305626)
- National Human Genome Research Institute (R01 HG003143)
- 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 contact maps, read mapping, quality control
- MeSH terms
- Algorithms, Alleles, Cell Line, Chromosomes, Humans, Software, Genomics
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
