CoolBox: a flexible toolkit for visual analysis of genomics data

Weize Xu,Gang Cao,Quan Zhong,Ya Zuo,Da Lin,Jinxia Dai,Guoliang Li

doi:10.1186/s12859-021-04408-w

Abstract

BackgroundData visualization, especially the genome track plots, is crucial for genomics researchers to discover patterns in large-scale sequencing dataset. Although existing tools works well for producing a normal view of the input data, they are not convenient when users want to create customized data representations. Such gap between the visualization and data processing, prevents the users to uncover more hidden structure of the dataset.ResultsWe developed CoolBox—an open-source toolkit for visual analysis of genomics data. This user-friendly toolkit is highly compatible with the Python ecosystem and customizable with a well-designed user interface. It can be used in various visualization situations like a Swiss army knife. For example, to produce high-quality genome track plots or fetch commonly used genomic data files with a Python script or command line, to explore genomic data interactively within Jupyter environment or web browser. Moreover, owing to the highly extensible Application Programming Interface design, users can customize their own tracks without difficulty, which greatly facilitate analytical, comparative genomic data visualization tasks.ConclusionsCoolBox allows users to produce high-quality visualization plots and explore their data in a flexible, programmable and user-friendly way.

Highlights

Data visualization, especially the genome track plots, is crucial for genomics researchers to discover patterns in large-scale sequencing dataset
With the rapid development of Next-Generation Sequencing (NGS) technologies, more and more genomic assays have been developed to profile the genome from various aspects, such as RNA expression [1], protein-DNA binding [2], chromatin accessibility [3] and 3D structure [4, 5]
Many visualization tools have been developed to meet these demands, and these tools can be classified into three categories: (1) Command-line plotting tool [10, 11], (2) Graphical User Interface(GUI) software [12], and (3) Web-based track browser [13,14,15]

Summary

Results

We developed CoolBox—an open-source toolkit for visual analysis of genomics data. This user-friendly toolkit is highly compatible with the Python ecosystem and customizable with a well-designed user interface. It can be used in various visualization situations like a Swiss army knife. To produce high-quality genome track plots or fetch commonly used genomic data files with a Python script or command line, to explore genomic data interactively within Jupyter environment or web browser. Owing to the highly extensible Application Programming Interface design, users can customize their own tracks without difficulty, which greatly facilitate analytical, comparative genomic data visualization tasks

Background

Results and discussion

Conclusion