ChromoMap: an R package for interactive visualization of multi-omics data and annotation of chromosomes

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36 Scopus citations


Background: The recent advancements in high-throughput sequencing have resulted in the availability of annotated genomes, as well as of multi-omics data for many living organisms. This has increased the need for graphic tools that allow the concurrent visualization of genomes and feature-associated multi-omics data on single publication-ready plots. Results: We present chromoMap, an R package, developed for the construction of interactive visualizations of chromosomes/chromosomal regions, mapping of any chromosomal feature with known coordinates (i.e., protein coding genes, transposable elements, non-coding RNAs, microsatellites, etc.), and chromosomal regional characteristics (i.e. genomic feature density, gene expression, DNA methylation, chromatin modifications, etc.) of organisms with a genome assembly. ChromoMap can also integrate multi-omics data (genomics, transcriptomics and epigenomics) in relation to their occurrence across chromosomes. ChromoMap takes tab-delimited files (BED like) or alternatively R objects to specify the genomic co-ordinates of the chromosomes and elements to annotate. Rendered chromosomes are composed of continuous windows of a given range, which, on hover, display detailed information about the elements annotated within that range. By adjusting parameters of a single function, users can generate a variety of plots that can either be saved as static image or as HTML documents. Conclusions: ChromoMap’s flexibility allows for concurrent visualization of genomic data in each strand of a given chromosome, or of more than one homologous chromosome; allowing the comparison of multi-omic data between genotypes (e.g. species, varieties, etc.) or between homologous chromosomes of phased diploid/polyploid genomes. chromoMap is an extensive tool that can be potentially used in various bioinformatics analysis pipelines for genomic visualization of multi-omics data.

Original languageEnglish
Article number33
JournalBMC Bioinformatics
Issue number1
StatePublished - Dec 2022

Bibliographical note

Funding Information:
CMRL is partially supported by the National Institute of Food and Agriculture, AFRI Competitive Grant Program Accession No. 1018617 and National Institute of Food and Agriculture, United States Department of Agriculture, Hatch Program Accession No. 1020852. The funding agencies did not have any role on the study and collection, analysis, and interpretation of data or in writing the manuscript.

Funding Information:
The authors would like to thank Professor Alan Bruce Downie (University of Kentucky) for reviewing the final draft of the manuscript. The authors would like to thank all the individuals who were involved in the creation of the publicly available datasets that were used as examples in this manuscript.

Publisher Copyright:
© 2022, The Author(s).


  • Genome visualization
  • Multi-omics data visualization
  • R package

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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