Abstract
Exponential growth of high-throughput data and the increasing complexity of omics information have been making processing and interpreting biological data an extremely difficult and daunting task. Here we developed FuncTree (http://bioviz.tokyo/functree), a web-based application for analyzing and visualizing large-scale omics data, including but not limited to genomic, metagenomic, and transcriptomic data. FuncTree allows user to map their omics data onto the “Functional Tree map”, a predefined circular dendrogram, which represents the hierarchical relationship of all known biological functions defined in the KEGG database. This novel visualization method allows user to overview the broad functionality of their data, thus allowing a more accurate and comprehensive understanding of the omics information. FuncTree provides extensive customization and calculation methods to not only allow user to directly map their omics data to identify the functionality of their data, but also to compute statistically enriched functions by comparing it to other predefined omics data. We have validated FuncTree’s analysis and visualization capability by mapping pan-genomic data of three different types of bacterial genera, metagenomic data of the human gut, and transcriptomic data of two different types of human cell expression. All three mapping strongly confirms FuncTree’s capability to analyze and visually represent key functional feature of the omics data. We believe that FuncTree’s capability to conduct various functional calculations and visualizing the result into a holistic overview of biological function, would make it an integral analysis/visualization tool for extensive omics base research.
Highlights
Recent advancement in high throughput DNA sequencing technology has lead to an exponential growth of omics information
Onto the Functional Tree, user can accurately identify the expression of overlapping functions, such as module and KEGG Orthology (KO) that are assigned to multiple different pathways
To evaluate the validity of FuncTree's mapping and analysis capability, we provide three case stories to illustrate the use of FuncTree by mapping genomic, metagenomic, and transcriptomic data
Summary
Recent advancement in high throughput DNA sequencing technology has lead to an exponential growth of omics information. The recent development of methodology such as metagenomic analysis, where biologists have to deal with the genetic information of multiple organisms and various meta-data, instead of a single cell or an organism, has lead to the increase complexity of omics information. In contrast to the advancement of high throughput sequencing technology, comprehending omics data in order to develop further biological insights is becoming an increasingly difficult and daunting task. FuncTree design, data collection and analysis, decision to publish, or preparation of the manuscript
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