ExpressAnalyst: A unified platform for RNA-sequencing analysis in non-model species

Peng Liu, Jessica Ewald, Zhiqiang Pang, Elena Legrand, Yeon Seon Jeon, Jonathan Sangiovanni, Orcun Hacariz, Guangyan Zhou, Jessica A. Head, Niladri Basu and Jianguo Xia ()
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Peng Liu: McGill University
Jessica Ewald: McGill University
Zhiqiang Pang: McGill University
Elena Legrand: McGill University
Yeon Seon Jeon: McGill University
Jonathan Sangiovanni: McGill University
Orcun Hacariz: McGill University
Guangyan Zhou: McGill University
Jessica A. Head: McGill University
Niladri Basu: McGill University
Jianguo Xia: McGill University

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract The increasing application of RNA sequencing to study non-model species demands easy-to-use and efficient bioinformatics tools to help researchers quickly uncover biological and functional insights. We developed ExpressAnalyst ( www.expressanalyst.ca ), a web-based platform for processing, analyzing, and interpreting RNA-sequencing data from any eukaryotic species. ExpressAnalyst contains a series of modules that cover from processing and annotation of FASTQ files to statistical and functional analysis of count tables or gene lists. All modules are integrated with EcoOmicsDB, an ortholog database that enables comprehensive analysis for species without a reference transcriptome. By coupling ultra-fast read mapping algorithms with high-resolution ortholog databases through a user-friendly web interface, ExpressAnalyst allows researchers to obtain global expression profiles and gene-level insights from raw RNA-sequencing reads within 24 h. Here, we present ExpressAnalyst and demonstrate its utility with a case study of RNA-sequencing data from multiple non-model salamander species, including two that do not have a reference transcriptome.

Date: 2023
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DOI: 10.1038/s41467-023-38785-y

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