metaprotr: R package for post-processing metaproteomics data

License: GPL v3


Set of tools for descriptive analysis of metaproteomics data generated from high-throughput mass spectrometry instruments. These tools allow to cluster peptides and proteins abundance, expressed as spectral counts, and to manipulate them in groups of metaproteins.

This information can be represented using multiple visualization functions to portray the global metaproteome landscape and to differentiate samples or conditions, in terms of abundance of metaproteins, taxonomic levels and/or functional annotation.

The provided tools allow to implement flexible analytical pipelines that can be easily applied to studies interested in metaproteomics analysis.

Application case

Pipeline to analyse the metaproteomes of gut microbiota

A curated R script is available with the detailed instructions to analyse intestinal microbiota.

Data inputs

The required files to use the package are :

  1. Peptide abundances expressed as spectral counts. This file is generated from X!Tandempipeline using an adapted iterative approach described by Bassignani, 2019. Contact PAPPSO for more details. This file should have the first seven columns named:
  1. List of protein names associated to the identified peptides. This file should have eight columns named:
  1. Metadata information. At least three columns must be present and named as:
  1. Catalog of genes with taxonomic annotations with the following format:
  1. Functional annotations of genes (optional). The functional annotations from the Kyoto Encyclopedia of Genes and Genomes (KEGG) were added to the IGC 9.9 database. DOI. This file should include two columns named:
Alt text


Checkout the documentation and the cheatsheet that displays the available functions on metaprotr.

Contribute to the project

Everybody is welcome to contribute to the metaprotr.

Indicate errors :warning: :bangbang:

If you found an error please describe it in the issues section and address it to the package mantainer.

Please provide the following information: * Summarize the bug encountered concisely. * What is the current bug behavior? * What is the expected correct behavior? * Describe the steps to reproduce it. * Paste logs and/or screenshots. * Add possible fixes.

Add modifications :star: :thumbsup:

To improve, modify or add a new feature/function to the project please follow this procedure:

  1. Create a new branch from “stable” and name it with the feature/function that you will work on.

  2. Make changes and commits to this branch while developing.

When making commits it is recommended to use the following graphical identifiers:

Identifier Code Description
:lollipop: : lollipop : Minor change (ex. comment, renaming)
:pencil2: : pencil2 : New code
:wrench: : wrench : Code refactoring
:checkered_flag: : checkered_flag : code test, check or verification
:bug: : bug : bug detected


  git commit -m ':pencil2: writing core logic of an awesome function'
  1. Make a pull request to the branch “stable”.