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Complex heatmaps reveal patterns and correlations in multidimensional genomic data
Open accessAbstract
Summary: Parallel heatmaps with carefully designed annotation graphics are powerful for efficient visualization of patterns and relationships among high dimensional genomic data. Here we present the ComplexHeatmap package that provides rich functionalities for customizing heatmaps, arranging multiple parallel heatmaps and including user-defined annotation graphics. We demonstrate the power of ComplexHeatmap to easily reveal patterns and correlations among multiple sources of information with four real-world datasets. Availability and Implementation: The ComplexHeatmap package and documentation are freely available from the Bioconductor project: http://www.bioconductor.org/packages/devel/bioc/html/ComplexHeatmap.html. Contact: m.schlesner@dkfz.de Supplementary information: Supplementary data are available at Bioinformatics online.
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Metadata
- Authors
- Gu, Z., Eils, R., & Schlesner, M.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-05-20
- Volume
- 32
- Issue
- 18
- Pages
- 2847-2849
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2406250479
- Cited by
- 10,034
- References
- 3
- FWCI
- 72.83
- Type
- journal article
- 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 ›
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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.
