RIdeogram: Drawing SVG graphics to visualize and map genome-wide data on the idiograms

Zhaodong Hao, Dekang Lv, Ying Ge, Jisen Shi, Dolf Weijers, Guangchuang Yu*, Jinhui Chen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

206 Citations (Scopus)

Abstract

Background. Owing to the rapid advances in DNA sequencing technologies, whole genome from more and more species are becoming available at increasing pace. For whole-genome analysis, idiograms provide a very popular, intuitive and effective way to map and visualize the genome-wide information, such asGCcontent, gene and repeat density, DNA methylation distribution, genomic synteny, etc. However, most available software programs and web servers are available only for a few model species, such as human, mouse and fly, or have limited application scenarios. As more and more non-model species are sequenced with chromosome-level assembly being available, tools that can generate idiograms for a broad range of species and be capable of visualizing more data types are needed to help better understanding fundamental genome characteristics. Results. The R package RIdeogram allows users to build high-quality idiograms of any species of interest. It can map continuous and discrete genome-wide data on the idiograms and visualize them in a heat map and track labels, respectively. Conclusion. The visualization of genome-wide data mapping and comparison allow users to quickly establish a clear impression of the chromosomal distribution pattern, thus making RIdeogram a useful tool for any researchers working with omics.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalPeerJ Computer Science
Volume6
DOIs
Publication statusPublished - 20 Jan 2020

Keywords

  • Chromosome
  • Data visualization
  • Genome
  • Idiogram
  • R package

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