The DOI matches its Crossref record.
regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests
Open accessAbstract
Motivation: Statistically assessing the relation between a set of genomic regions and other genomic features is a common challenging task in genomic and epigenomic analyses. Randomization based approaches implicitly take into account the complexity of the genome without the need of assuming an underlying statistical model. Summary: regioneR is an R package that implements a permutation test framework specifically designed to work with genomic regions. In addition to the predefined randomization and evaluation strategies, regioneR is fully customizable allowing the use of custom strategies to adapt it to specific questions. Finally, it also implements a novel function to evaluate the local specificity of the detected association. Availability and implementation: regioneR is an R package released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/regioneR). Contact: rmalinverni@carrerasresearch.org
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
No references could be resolved yet.
Research works printed but not linked: 7
- De, 2013, The dilemma of choosing the ideal permutation strategy while estimating statistical significance of genome-wide enrichment, Brief. Bioinform.
- Favorov, 2012, Exploring massive, genome scale datasets with the genometricorr package, PLoS Comput. Biol., 8, e1002529, 10.1371/journal.pcbi.1002529 · DOI · Paper page
- Heger, 2013, GAT: a simulation framework for testing the association of genomic intervals, Bioinformatics, 29, 2046, 10.1093/bioinformatics/btt343 · DOI · Paper page
- Lawrence, 2009, rtracklayer: An R package for interfacing with genome browsers, Bioinformatics, 25, 1841, 10.1093/bioinformatics/btp328 · DOI · Paper page
- Lawrence, 2013, Software for computing and annotating genomic ranges, PLoS Comput. Biol., 9, 1, 10.1371/journal.pcbi.1003118 · DOI · Paper page
- Phipson, 2010, Permutation P-values should never be zero: calculating exact p-values when permutations are randomly drawn, Stat. Appl. Genet. Mol. Biol., 9, 39, 10.2202/1544-6115.1585 · DOI · Paper page
- Wu, 2010, Redefining CpG islands using hidden Markov models, Biostatistics, 11, 499, 10.1093/biostatistics/kxq005 · DOI · Paper page
Cited by
Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.036 · Cited by 2,321
“A permutation-based approach with 1,000 random permutations was used to determine statistical significance of the overlap between genomic coordinates for GER and NC genes with CHD8-binding sites using the R package regioneR (Gel et al., 2016).”
MethodExploring Epigenomic Datasets by ChIPseeker
Wang, Q., Li, M., Wu, T., Zhan, L., Li, L., Chen, M., Xie, W., Xie, Z., Hu, E., Xu, S., et al. (2022) · Current Protocols · doi:10.1002/cpz1.585 · Cited by 415
m6A RNA methylation regulates the fate of endogenous retroviruses
Chelmicki, T., Roger, E., Teissandier, A., Dura, M., Bonneville, L., Rucli, S., Dossin, F., Fouassier, C., Lameiras, S., & Bourc’his, D. (2021) · Nature · doi:10.1038/s41586-020-03135-1 · Cited by 307
Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis
Fiorito, G., the BIOS Consortium, the Lifepath consortium, McCrory, C., Robinson, O., Carmeli, C., Rosales, C. O., Zhang, Y., Colicino, E., Dugué, P.-A., et al. (2019) · Aging · doi:10.18632/aging.101900 · Cited by 219
Fiorito, G., Caini, S., Palli, D., Bendinelli, B., Saieva, C., Ermini, I., Valentini, V., Assedi, M., Rizzolo, P., Ambrogetti, D., et al. (2021) · Aging Cell · doi:10.1111/acel.13439 · Cited by 202
Metadata
- Authors
- Gel, B., Díez-Villanueva, A., Serra, E., Buschbeck, M., Peinado, M. A., & Malinverni, R.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-09-30
- Volume
- 32
- Issue
- 2
- Pages
- 289-291
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2180834397
- Cited by
- 577
- References
- 0
- FWCI
- 7.20
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests. https://app.cochat.ai/papers/10.1093/bioinformatics/btv562
- The paper
- Gel, B., Díez-Villanueva, A., Serra, E., Buschbeck, M., Peinado, M. A., & Malinverni, R. (2016). regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests. Bioinformatics. https://doi.org/10.1093/bioinformatics/btv562
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.
