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

doi:10.7717/peerj-cs.251

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

PeerJ Comput Sci. 2020 Jan 20:6:e251. doi: 10.7717/peerj-cs.251. eCollection 2020.

Authors

Zhaodong Hao^1

2, Dekang Lv³, Ying Ge³, Jisen Shi¹, Dolf Weijers², Guangchuang Yu⁴, Jinhui Chen¹

Affiliations

¹ Key Laboratory of Forest Genetics & Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu, China.
² Laboratory of Biochemistry, Wageningen University, Wageningen, Haarlem, Netherlands.
³ Institute of Cancer Stem Cell, Dalian Medical University, Dalian, Liaoning, China.
⁴ Institute of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China.

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 as GC content, 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.

Keywords: Chromosome; Data visualization; Genome; Idiogram; R package.

Grants and funding

This work was supported by the Key Research and Development Plan of Jiangsu Province (BE2017376), the Foundation of Jiangsu Forestry Bureau (LYKJ[2017]42), the Qinglan Project of Jiangsu Province and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.