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

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 m...

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Bibliographic Details
Published in:BMC bioinformatics Vol. 23; no. 1; pp. 33 - 9
Main Authors: Anand, Lakshay, Rodriguez Lopez, Carlos M.
Format: Journal Article
Language:English
Published: London BioMed Central 11.01.2022
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Algorithms
Analysis
Annotations
Archives & records
Bioinformatics
Biomedical and Life Sciences
Chromatin
Chromosome mapping
Chromosomes
Chromosomes - genetics
Computational Biology
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Data visualization
Datasets
Diploids
DNA methylation
Economic aspects
Gene expression
Gene mapping
Genome
Genome visualization
Genomes
Genomic analysis
Genomics
Genotypes
High-throughput screening (Biochemical assaying)
Homology
Innovations
JavaScript
Life Sciences
Methods
Microarrays
Microsatellites
Multi-omics data visualization
Next-generation sequencing
Peptide mapping
Polyploidy
R package
Software
Technology application
Transcriptomics
Visualization
United States
Multi-omics data visualization
Genome visualization
R package
ISSN:1471-2105, 1471-2105
Online Access:Get full text
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Summary: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.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-021-04556-z