OmicCircos: A Simple-to-Use R Package for the Circular Visualization of Multidimensional Omics Data

Introduction

Visualization is an essential aspect of the statistical analysis of large-scale genomic data collections. It plays important roles in exploring, analyzing, and presenting patterns and correlations found in multidimensional genomic data. ¹ The circular plot with multiple “doughnut” tracks is particularly effective in displaying relationships among genes or genomic intervals. The software package Circos, written in Perl, is widely used to generate circular plots. ² It has been cited in more than 300 publications describing the landscape of genomic alterations including mutations, aberrant expression patterns, CNVs, methylation patterns, and other types of structural variation (http://circos.ca). However, while Circos is flexible and quite powerful, it demands that users conquer a steep learning curve. Other less well-known Java-based circular plot tools, such as CGView and DNAplotter,^3,4 are also known to be less than completely user-friendly.

In efforts to develop more efficient software programs for generating circular plots, researchers have looked to the R package, a common environment for statistical computing and graphic visualization of large genomic data sets. ⁵ The recently published R package Rcircos incorporates standard R graphics into a circular ideogram, but lacks detailed visualization functions like zoom and independent track drawing. ⁶ Another application, ggbio, has very limited circular plot functionality since it utilizes a third-party graphic tool called ggplot. ⁷ Clearly, a distinct need exists for a software package for generating circular plots with readily customizable features that can help scientists more easily display and communicate complex genomics data.

Here, we present OmicCircos, a simple and comprehensive approach to creating circular plots. The software package offers end users four unique customizable capabilities, all of which are available through a single command: •

Independent track plotting and modification that does not affect other tracks in a given plot;

This last capability results from the integration and use of the GenomicRanges package in Bioconductor within the OmicCircos environment.

Features

The OmicCircos package performs three main functions: 1)

segAnglePo() specifies the circle size, number of segments, and segment width. The package includes chromosome size data for human genome hg19/hg18 and mouse genome mm10/mm9. Such data are typically used to plot the outermost circle, which serves as an anchor for the figure. Alternatively, if the figure is intended to represent a set of genes rather than a whole genome, the user can define one segment per gene by simply constructing the frame data with gene names and segment sizes. segAnglePo() can also read data from the GRanges object generated by the GenomicRanges package in Bioconductor, which allows genomic intervals and annotations to be easily manipulated.

Examples

To demonstrate the functionality of the OmicCircos package, we display The Cancer Genome Atlas (TCGA) data describing breast cancer genomic variations such as mutation, expression, and copy number previously reported by the TCGA Network, ⁸ as well as putative fusion proteins that were identified in house from TCGA breast cancer RNAseq data using deFuse. ⁹ Figure 1 illustrates an OmicCircos plot consisting of two halves: the right half displays gene expression, CNV, correlation of CNV and expression, and fusion proteins for 15 Her2 subtype samples; the left half shows the zoom image of chromosomes 11 and 17 to demonstrate the focal copy number amplifications in the region of CDC6, ERBB2, and CCND1. The gene-expression heatmap uses a position-independent display for a better representation of gene-dense areas. The actual gene positions are linked to chromosomes with elbow connectors.

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Figure 1.

Circular plots by OmicCircos of expression, CNV, and fusion proteins in 15 Her2 subtype samples from TCGA breast cancer data. ⁸ Circular tracks from outside to inside: genome positions by chromosomes (black lines are cytobands), expression heatmap of 2000 most variable genes whose locations are indicated by elbow connectors, CNVs (red: gain, blue: loss), correlation p-values between expression and CNV, fusion proteins (intra/inter chromosomes: red/blue). Chromosomes 1–22 are shown in the right half of the circle. Zoomed chromosomes 11 and 17 are displayed in the left half. The circle arc was drawn using trigonometric functions. The fusion protein links were plotted with the Bέzier curve algorithm.

The circular plot from the OmicCircos package can be seamlessly integrated with other types of R statistical graphics. For example, Figure 2 illustrates CNV and gene-expression data for the four breast cancer subtypes: Basal, Her2, Luminal A (LumA) and Luminal B (LumB) with 15 samples in each group. CNVs for each subtype are represented in individual tracks. Principal component analysis (PCA) of gene-expression data for the four subtypes is represented in the center of the figure. Distinct patterns of arm-level CNV gain or loss are visible, eg, 5q loss in Basal, 16q loss in Luminal A/B, and 10p gain in Basal. More examples of circular plots generated using OmicCircos package are available in the package vignette. These show comparative genomic analyses, expression quantitative trait loci (eQTLs), protein-protein interactions (PPIs), and gene interactions within the context of pathways.

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Figure 2.

Integration of circular plots by OmicCircos and clusters from R of TOGA breast cancer data. Circular tracks from outside to inside: genome positions by chromosomes (black lines are cytobands), CNVs in Basal, Her2, Luminal A (LumA) and Luminal B (LumB) subtypes with 15 samples in each track (red: gain; blue: loss), in the center, four clusters from principle component analysis (PCA) of the gene expression data with R packages in the bioconductor.

Conclusion

The OmicCircos package offers researchers a highly efficient, user-friendly program and visualization tool that not only illustrates genomic data analyses but also carries out statistical analyses that can be combined to generate publication-ready circular plots for a wide range of data types. Besides these functionalities, OmicCircos also takes advantage of statistical functions and comprehensive genome annotation packages in the R/Biocondutor environment. This makes the package a powerful circular plot tool that provides users with unique functions that include independent track drawing, zooming, easy genome annotation manipulation, and integration of statistical analysis and graphics. OmicCircos has sufficient flexibility to integrate with packages in R/Bioconductor that bring together annotation, analysis, and comparative genomics pipelines.

Author Contributions

Conceived and designed the experiments: YH, CY. Analyzed the data: YH, C-HH, KN. Wrote the first draft of the manuscript: YH, CY. Contributed to the writing of the manuscript: YH, CY, C-HH, Q-RC, DM. Agree with manuscript results and conclusions: YH, CY, C-HH, Q-RC, KN, GAK, DM. All authors reviewed and approved of the final manuscript.

Disclosures and Ethics

As a requirement of publication the authors have provided signed confirmation of their compliance with ethical and legal obligations including but not limited to compliance with ICMJE authorship and competing interests guidelines, that the article is neither under consideration for publication nor published elsewhere, of their compliance with legal and ethical guidelines concerning human and animal research participants (if applicable), and that permission has been obtained for reproduction of any copyrighted material. This article was subject to blind, independent, expert peer review. The reviewers reported no competing interests.