metaQuantome is a software suite that enables the quantitative analysis, statistical evaluation. and visualization of mass-spectrometry-based metaproteomics data. In the latest update of this software, we have provided several extensions, including a step-by-step training guide, the ability to perform statistical analysis on samples from multiple conditions, and a comparative analysis of metatranscriptomics data. The training module, accessed via the Galaxy Training Network, will help users to use the suite effectively both for functional as well as for taxonomic analysis. We extend the ability of metaQuantome to now perform multi-data-point quantitative and statistical analyses so that studies with measurements across multiple conditions, such as time-course studies, can be analyzed. With an eye on the multiomics analysis of microbial communities, we have also initiated the use of metaQuantome statistical and visualization tools on outputs from metatranscriptomics data, which complements the metagenomic and metaproteomic analyses already available. For this, we have developed a tool named MT2MQ ("metatranscriptomics to metaQuantome"), which takes in outputs from the ASaiM metatranscriptomics workflow and transforms them so that the data can be used as an input for comparative statistical analysis and visualization via metaQuantome. We believe that these improvements to metaQuantome will facilitate the use of the software for quantitative metaproteomics and metatranscriptomics and will enable multipoint data analysis. These improvements will take us a step toward integrative multiomic microbiome analysis so as to understand dynamic taxonomic and functional responses of these complex systems in a variety of biological contexts. The updated metaQuantome and MT2MQ are open-source software and are available via the Galaxy Toolshed and GitHub.
Bibliographical noteFunding Information:
We thank the European Galaxy team for the support during Galaxy implementation. We also thank Dr. Björn A. Grüning (University of Freiburg, Germany) for helping us during the implementation of the workflow in the European Galaxy platform. We acknowledge funding for this work from the National Cancer Institute - Informatics Technology for Cancer Research (NCI-ITCR) grant 1U24CA199347 and from a grant through the Norwegian Centennial Chair (NOCC) program at the University of Minnesota to T.J.G. and M.Ø.A. The European Galaxy server that was used for data analysis is partially funded by the Collaborative Research Centre 992 Medical Epigenetics (DFG grant SFB 992/1 2012) and the German Federal Ministry of Education and Research (BMBF grants 031 A538A/A538C RBC, 031L0101B/031L0101C de.NBI-epi, and 031L0106 de.STAIR (de.NBI)).
© 2021 American Chemical Society.
- bioinformatics software
- functional inference
- mass spectrometry
- time course
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't