SOFIA: An R Package for Enhancing Genetic Visualization With Circos (2024)

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Abstract

Introduction

Visualization is one of the best strategies for exploring, analyzing, and presenting data in common genetic and genomic studies such as linkage mapping, quantitative trait loci (QTL) mapping, association studies, and comparative genomics. These types of genetic analyses, especially those related to genetic mapping, generally involve a series of methodological steps such as creation of mapping populations, defining the type and number of markers to use, data cleaning, estimation of recombination, linkage group ordering and alignment, phenotyping, and the evaluation of the genotype–phenotype associations. Each step contains its own potential sources of error, and data visualization is an important means for detecting the introduced error and ensuring the resulting accuracy and reproducibility of the study.

Most packages and/or software for genetic analysis possess visualization tools for exploring general aspects of the data. For example, the commercial software, JoinMap (Stam 1993), which is widely used for genetic map construction, can display constructed linkage groups, alignments of linkage groups to compare marker position and linkage group structure between populations or species, and colorized phased genotypic data to facilitate exploration of recombination events and to detect genotyping errors in the mapping population. Other software for performing QTL and genome-wide association studies (GWAS), such as MapQTL (Van Ooijen 2009), r/qtl (Broman et al. 2003), and sommer (Covarrubias-Pazaran 2016), provide functions for plotting LOD scores and P-values for detecting genotype–phenotype associations. However, integrating and arranging data from these genetic software and independent genetic analyses into single aesthetical images for simultaneous visualization remains challenging.

Circos (Krzywinski et al. 2009) is a novel software that addresses the challenges in visualizing genetic data by creating circular ideograms composed of “2D tracks” of heatmaps, scatter plots, line plots, histograms, links between common markers, glyphs, text, etc. The flexibility of the software makes it suitable for rapid deployment in linkage and QTL mapping analyses and is especially useful for comparing genetic data between individuals, populations, and species. Circos, an open-source tool, has proven to be one of the most effective ways to display high-dimensional data, and it is one of the most used software (i.e., more than 2200 citations) for visualization in genetic and genomic research. However, the Perl-native Circos operates through a command-line interface that, while highly flexible, requires the user to have advanced computational skills. For users with little programming experience, this remains an obstacle to the routine implementation of Circos for data exploration and figure development.

In this paper, we present the R package SOFIA, which is a powerful tool for visualizing genetic data that combines the advantages of the R programming language and Circos. Our package provides a pipeline for producing high quality images with the potential to integrate high-dimensional genetic data in an aesthetical and highly useful manner. Most importantly, unlike other available software, SOFIA is a tool that exploits most of the capabilities of Circos, but integrates it within the friendlier R programming language to allow simultaneous data analysis and visualization in a single programming environment.

Software Similar to SOFIA

To facilitate the use of Circos, additional tools such as Circoletto (Darzentas 2010), ClicO FS (Cheong et al. 2015) and RCircos (Zhang et al. 2013) have recently been created. These software packages aim to provide a more user-friendly interface for using Circos. Unfortunately, these tools lack some of the qualities and essential attributes of Perl-native Circos such as the flexibility, automatization, image quality, and robustness. For example, because running Circos from the command line can be challenging for computationally inexperienced users, tools like ClicO FS (Cheong et al. 2015) and Circoletto (Darzentas 2010) use a graphical interface (GUI) to facilitate the generation of Circos-like figures. While is true that the GUIs allow the easy formatting and structuration of the data for plotting Circos-like figures, these particular software remain too inflexible in terms of automatization, scalability, and personalization necessary for data exploration during preliminary analysis and final figure preparation. In fact, plotting recombination blocks (as heatmaps) for linkage groups in a genetic map with 1000 markers and 100 plants, a common preliminary analysis to identify genotyping errors leading to potentially false double-recombination events, could take a considerable amount of time if a GUI is used (plus the amount of time required for preparing all the numeric data files). The other available software, RCircos (Zhang et al. 2013), runs completely within the R programming language and produces Circos-like figures in a more semi-automatized fashion, but it is very inflexible and lacks the formatting and configuration capabilities (e.g., color configuration is specified at plot-type level instead of at the individual track level) and the resulting figures tend to be of lower quality compared to those produced by Perl-native Circos (Figure 1).

Features and Functionality of SOFIA

SOFIA is a package that produces high-quality figures by creating all the configuration files and numeric data required to automatically run Perl-native Circos from R. Most of the functionality of Circos is accessible through SOFIA, including all 2D tracks (scatter plots, line plots, glyphs, text, links, histograms, and heatmaps), formatting, figure general configuration, etc. However, several characteristics of Perl-native Circos are not directly available in SOFIA. In this case, a single argument in the SOFIA package provides advanced users the ability to simplify the creation of all their configuration and numeric data files without invoking Circos. SOFIA-generated configuration and numeric data files can be further edited manually to add parameters not supported in SOFIA, and then used to run Perl-native Circos directly instead of using SOFIA. Similarly, some of the SOFIA’s functionalities are not implemented exactly as in Perl-native Circos. For example, rules are not supported in SOFIA; however, they can be implemented by using multiple plots in a loop in which each plot consists in data points that meet certain rule, and thus they can be configured individually in terms of color, location, plot type, etc. In the Perl-native Circos version, automatic track plotting is supported, which facilitates the rapid configuration of data sets from multiple genetic analyses. In SOFIA, this feature can be implemented by simply iterating in R the data to be plotted as well as the location and formatting of the tracks in the circular ideogram. An important application of this approach is exploited, for example, for constructing representations of genetic linkage blocks (by using heatmaps). In terms of organization, it is very straightforward to work with many Circos figures in SOFIA since a single script (with very few code lines) may contain all the required instructions to generate the figures without further manual intervention. Thus, SOFIA provides a mid-level platform for easily (compared with other Circos-related software) generating high-quality Circos figures while maintaining most of the capabilities and functionality related to formatting and flexibility (Table 1). Since SOFIA operates as an R interface, Perl-native Circos has to be installed separately according with the author’s instructions (For more details, please see www.circos.ca).

To take advantage of the help resources and tutorials available for operating Circos (http://circos.ca/documentation/tutorials), we kept as much of the Circos syntax and logical flow in SOFIA as possible, especially in regards to formatting (e.g., color schemas). In our website (https://cggl.horticulture.wisc.edu/software/), we provide a library of figure templates that we have found to be very useful for exploring and analyzing data from linkage mapping, association studies, or many other genomic studies. For further SOFIA versions, newer templates will added. In this paper, we also provide samples of the figures produced by SOFIA as well as the R code for generating them (Figures 1–3; Supplementary File 1).

In Figure 2, we show a typical example of how comparisons of marker-trait associations between genetic maps for 2 species or populations (with 12 and 9 linkage groups [LGs] each) can be visualized by using SOFIA. On each map, we display the presence/absence of genetic markers (black lines) as well as labels for randomly-selected positions (Figure 2A). Additionally, 3 plots (2 scatter plots and a line plot) display log-transformed P-values scores from a GWAS study across all the LGs (Figure 2B–D) followed by links connecting common markers between genetic maps and colored according to the linkage group in one of the maps (Figure 2E).

As we previously mentioned, SOFIA offers multiple options for plotting and formatting data in many different ways. Figure 3 serves as an example of a more complex figure that could be generated for publication purposes. In this figure, we show different types of data for 2 genetic maps; in the outer ring, a histogram showing the marker density is displayed (Figure 3A), followed by 2 heatmaps (in blue and purple) with random data (Figure 3B). Subsequently, a ring with datasets plotted as lines in different colors (Figure 3C) and 2 scatter plots in which the centromeric region is highlighted in darker grey color (Figure 3D). In the inner part of the figure, labels for randomly-selected markers are displayed (Figure 3E), followed by recombination blocks for 74 genotypes (Figure 3F). The “recombination blocks” plot type is one the most useful tools incorporated in SOFIA, which only requires a phased-allele matrix for all the markers in the map (in Figure 3F, light and dark grey color coding represents allele absence and presence, respectively). After the recombination blocks, a set of tiles in different colors represents the genes across the linkage groups in one of the maps (Figure 3G). Finally, links connecting similar markers between maps are drawn in the interior of the figure (Figure 3H).

Conclusions

SOFIA is an R package for running Perl-native Circos within the R programming environment to display highly dimensional genetic data. By integrating R and Circos, the package combines several advantages unavailable in other software packages. For example, SOFIA provides flexible formatting configuration and different plot styles for data exploration and for creating publication quality figures. It does not require users to have advanced computational abilities, but at the same time, it offers the possibility for experienced programmers and those familiar with Perl-native Circos to fully exploit the advantages of R to acquire complex figures. Finally, SOFIA fills a gap between the highly specialized but difficult to implement software Circos, and those such as ClicO FS, which are interactive and user friendly but also inflexible in terms of automatization.

Availability and Requirements

Project name: SOFIA: an R package for enhancing genetic visualization

Project home page: https://cran.r-project.org and https://cggl.horticulture.wisc.edu/software/

Operating system(s): Unix and Windows systems

Programming language: R

Other requirements: R > 2.0 and Circos

License: GPL-3

Supplementary Material

Supplementary data is available at Journal of Heredity online.

Funding

This project was supported by USDA-ARS (project no. 3655-21220-001-00 provided to J.Z.); WI-DATCP (SCBG Project #14-002); Ocean Spray Cranberries, Inc.; Wisconsin Cranberry Growers Association; Cranberry Institute. B.S. was supported by the Frank B. Koller Cranberry Fellowship Fund for Graduate Students; G.C.P. and L.D.G. were supported by the Consejo Nacional de Ciencia y Tecnología (Mexico).

Acknowledgments

L.D.G., G.C.P., B.S., and J.Z. conceived the outline and main purpose of the software; L.D.G. designed and implemented the software package; G.C.P. participated in the software design and test. J.Z. and B.S. critically revised the manuscript. L.D.G. and B.S. wrote the manuscript. All authors read and approved the final manuscript. JZ and BS wish to express their gratitude through 1 Cor 10:31. L.D.G. wants to thank Martin Krzywinski for his advice and comments. We thank the anonymous reviewers who helped enhance the quality of this paper.

References

Author notes

Corresponding Editor: C. Titus Brown

© The American Genetic Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

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