MetaProSIP: automated inference of elemental fluxes in microbial communities

MetaProSIP has been integrated as TOPP util into OpenMS. No additional installer is required anymore.

Requirements:

  • High-Resolution MS, CID or HCD MS2
  • Developed and tested on orbitrap instruments
  • MS1 and MS2 need to be centroided (either on acquisition, conversion or in a workflow using the TOPP tool HiResPeakPicker)

For additional information on sample handling and acquisition please refer to the original publication.

Raw files:

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD000382.

Publications:
@article{sachsenberg2014metaprosip,
title={MetaProSIP: automated inference of stable isotope incorporation
 rates in proteins for functional metaproteomics},
author={Sachsenberg, Timo and Herbst, Florian-Alexander and Taubert, Martin and Kermer, Ren{\'e}
 and Jehmlich, Nico and von Bergen, Martin and Seifert, Jana and Kohlbacher, Oliver},
journal={Journal of proteome research},
year={2014},
publisher={ACS Publications}
}

FAQ:

  • Q: I get an “Error: Process returned with non 0 status.“ “Error: File not found (the file ‘C:/Users/USER/AppData/Local/Temp/cluster_result_15NMix_1_3_a_picked_yD9N.dat’ could not be found)“.
  • A: Make sure that a suitable R version (32 bit) and the R packages are installed and add the directory to you PATH environment variable.

If you want to use the original binaries and data of the original publication you may download the files below:

Download sample data and TOPPAS workflows:
MetaProSIP sample data
Please note that experimental data (mzML files) have already been picked to reduce the size of the file.

Example output and quality control report for 15N mix dataset (replicate a, 1:3):
MetaProSIP quality control report

Download Win64 installer of the original publication:
Win64 installer
Note that MetaProSIP requires R installed and accessible via the path environment variable.
Additionally, following R libraries need to be installed:
gplots
fpc
clValid