Meet MAPLE!

A flexible Microbiome Analysis PipeLinE for human gut metaproteomics

Thank you for your interest in using Microbiome Analysis Pipeline (MAPLE) in your microbiota study!

Please cite: Huang W, Kane MA. MAPLE: A Microbiome Analysis Pipeline Enabling Optimal Peptide Search and Comparative Taxonomic and Functional Analysis. J Proteome Res. 2021 doi: 10.1021/acs.jproteome.1c00114. PMID: 33848166.

MAPLE is able to generate an optimal metaproteomic search space for peptide identification without requiring matched metagenomic data and significantly increase search sensitivity while still maintaining a true low FDR. It can also compare the taxonomic and functional makeup between microbiota using a lowest common ancestor and gene ontology enrichment analysis with statistical support.

To start, please simply click the link below to download the latest version of MAPLE:

Read me first: A Step-by-Step Guide to Using MAPLE

Download MAPLE version 1.1.19 (updated on 5/6/2021)

Download sample data for database creation and enrichment analysis

System requirements

Enrichment analysis only: 32 or 64-bit Windows 7 or 10, high speed Internet connection, 2 GHz dual-core CPU, 2 GB of RAM, 2 GB of free disk space.

Metaproteomics minimum: 64-bit Windows 7, 2.5 GHz quad-core CPU, 10 GB of free disk space, 32 GB of free RAM to process a single file.

Metaproteomics recommended: 64-bit Windows 10, 3.5 GHz octa-core CPU, 20 GB of free disk space, 128 GB of free RAM or above to process multiple files.

Please note: To avoid incomplete search due to insufficient memory, 256 GB of free RAM or more may be required for analysis of large data sets.

To annotate microbiome peptides via web service, please visit our Microbiome Annotation of TaxoNomy and Gene Ontology (MANGO) server at http://mango.rx.umaryland.edu/.

If you have any questions or suggestions about MAPLE, please contact the developer at the mass spec center:

Weiliang Huang, Ph.D. (mscenter@rx.umaryland.edu)

This project is supported by the University of Maryland School of Pharmacy Mass Spectrometry Center grant SOP1841-IQB2014.