plotgardener: Coordinate-based Genomic Visualization in R

Plotgardener is a genomic data visualization package that enables users to programmatically generate complex, multi-panel figures with flexibility and precision. Employing a coordinate-based plotting system, plotgardener allows for exquisite control over plot sizes, positions, and arrangements through a user-defined page with explicit units of measurement. Its edge-to-edge, containerized visualizations preserve the mapping between user-specified containers and the represented data, ensuring accurate alignment of plots in the same genomic region. Operating entirely within the R environment, Plotgardener is optimized to quickly and easily read, plot, and arrange multi-omic data for an endless number of use cases.

Website GitHub

bedtoolsR: An R package for genomic data analysis and manipulation

The sequencing of the human genome and subsequent advances in DNA sequencing technology have created a need for computational tools to analyze and manipulate genomic data sets. The bedtools software suite and the R programming language have emerged as indispensable tools for this purpose but have lacked integration. Bedtoolsr is an R package that provides simple and intuitive access to all bedtools functions from within the R programming environment. We provide several usability enhancements, support compatibility with past and future versions of bedtools, and include unit tests to ensure stability. Bedtoolsr provides a user-focused, harmonious integration of the bedtools software suite with the R programming language that should be of great use to the genomic community.

Website GitHub Paper

CoralP: Clear and customizable visualization of the human phosphatome

CoralP is a user-friendly interactive web application for visualizing both quantitative and qualitative data. Qualitative and quantitative features can be represented in branch colors, node colors, and node sizes. Phosphatases can be organized using the published phosphatome tree or as radial or force directed networks. CoralP is simple to use, well documented, and freely available. It is the first and only dedicated tool for phosphatome visualization and is widely applicable to a variety of data types including those generated from proteomic, genomic, epidemiological, and high-throughput screening experiments.

Web App GitHub Preprint Paper

Coral: Clear and customizable visualization of human kinome data

Coral is a user-friendly interactive web application for visualizing both quantitative and qualitative data. Unlike previous tools, Coral can encode data in three features (node color, node size, and branch color), allows three modes of kinome visualization (the traditional kinome tree as well as radial and dynamic-force networks) and generates high-resolution scalable vector graphic files suitable for publication without the need for refinement in graphic editing software. Due to its user-friendly, interactive, and highly customizable design, Coral is broadly applicable to high-throughput studies of the human kinome.

Web App GitHub Preprint Paper

Mango: a bias-correcting ChIA-PET analysis pipeline

Chromatin Interaction Analysis by Paired-End Tag sequencing (ChIA-PET) is an established method for detecting genome-wide looping interactions at high resolution. Current ChIA-PET analysis software packages either fail to correct for non-specific interactions due to genomic proximity or only address a fraction of the steps required for data processing. Mango is a complete ChIA-PET data analysis pipeline that provides statistical confidence estimates for interactions and corrects for major sources of bias including differential peak enrichment and genomic proximity.

GitHub Paper

Sushi: flexible, quantitative and integrative genomic visualizations for publication-quality multi-panel figures

Interpretation and communication of genomic data require flexible and quantitative tools to analyze and visualize diverse data types, and yet a comprehensive tool to display all common genomic data types in publication quality figures does not exist to date. To address this shortcoming, we present Sushi.R, an R/Bioconductor package that allows flexible integration of genomic visualizations into highly customizable, publication-ready, multi-panel figures from common genomic data formats including Browser Extensible Data (BED), bedGraph, and Browser Extensible Data Paired-End (BEDPE).