Anjun Ma1, Minxuan Sun2, Adam McDermaid1,3, Bingqiang Liu4, Qin Ma1. 1. Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA. 2. Department of Computer Science, South Dakota State University, Brookings, SD, USA. 3. Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA. 4. School of Mathematics, Shandong University, Jinan, China.
Abstract
MOTIVATION: Metagenomic and metatranscriptomic analyses can provide an abundance of information related to microbial communities. However, straightforward analysis of this data does not provide optimal results, with a required integration of data types being needed to thoroughly investigate these microbiomes and their environmental interactions. RESULTS: Here, we present MetaQUBIC, an integrated biclustering-based computational pipeline for gene module detection that integrates both metagenomic and metatranscriptomic data. Additionally, we used this pipeline to investigate 735 paired DNA and RNA human gut microbiome samples, resulting in a comprehensive hybrid gene expression matrix of 2.3 million cross-species genes in the 735 human fecal samples and 155 functional enriched gene modules. We believe both the MetaQUBIC pipeline and the generated comprehensive human gut hybrid expression matrix will facilitate further investigations into multiple levels of microbiome studies. AVAILABILITY AND IMPLEMENTATION: The package is freely available at https://github.com/OSU-BMBL/metaqubic. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Metagenomic and metatranscriptomic analyses can provide an abundance of information related to microbial communities. However, straightforward analysis of this data does not provide optimal results, with a required integration of data types being needed to thoroughly investigate these microbiomes and their environmental interactions. RESULTS: Here, we present MetaQUBIC, an integrated biclustering-based computational pipeline for gene module detection that integrates both metagenomic and metatranscriptomic data. Additionally, we used this pipeline to investigate 735 paired DNA and RNA humangut microbiome samples, resulting in a comprehensive hybrid gene expression matrix of 2.3 million cross-species genes in the 735 human fecal samples and 155 functional enriched gene modules. We believe both the MetaQUBIC pipeline and the generated comprehensive human gut hybrid expression matrix will facilitate further investigations into multiple levels of microbiome studies. AVAILABILITY AND IMPLEMENTATION: The package is freely available at https://github.com/OSU-BMBL/metaqubic. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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