Based on OpenMS, a full SRM quantitation and quality control suite was developed by DTU BioSustain. It provides a standalone GUI for easy, fast, and scalable analysis of high-throughput metabolomics SRM experiments. It also added a set of state-of-the-art peak integration and peak alignment algorithms to the library. Check it out on GitHub!
Thanks for your interest in OpenNuXL - our novel Protein-nucleic acid cross-linking search engine. It will be soon fully integrated into an official OpenMS release and all source code will be made available. Prior to publication, installers (and source code) are available on request: please contact sachsenb (at) informatik.uni-tuebingen.de
Introduction EPIFANY is a protein inference engine based on a Bayesian network. Currently, a similar model to Fido is used with the main parameters alpha (pep_emission), beta (pep_spurious_emission) and gamma (prot_prior). If not specified, these parameters are trained based on their classification performance and calibration via a grid search by simply running with several possible [...]
FLASHDeconv 2.0 beta We are happy to announce the release of FLASHDeconv 2.0 beta version! FLASHDeconv 2.0 is almost twice faster than the previous version, for most datasets. It also has significantly better specificity and much less harmonic artifacts. In addition, the new quality score for each mass, called QScore, is introduced. QScore is the [...]
NASE is now included in OpenMS release, 2.5. Requirements: HCD (or ETD) data of RNA oligonucleotides acquired on a high-resolution mass spectrometer Fragment spectra (MS/MS) need to be centroided (either on acquisition, conversion, or in a workflow using the TOPP tool PeakPickerHiRes) Developed and tested on Linux (Ubuntu 18.04 and 18.10) systems with data from [...]
OpenPepXL: an open source peptide cross-link identification tool OpenPepXL is a protein-protein cross-link identification tool implemented in C++ as part of OpenMS. It works with all uncleavable labeled and label-free cross-linkers but not (yet) with cleavable ones. Requirements The current version of OpenPepXL, version 1.1 is available as part of OpenMS 2.5. Installers for Windows, [...]
RNPxl has been integrated into OpenMS and also the Proteome Discoverer Community Nodes. No custom installer is required anymore. Requirements: HCD data acquired on a high-resolution MS Developed and tested on orbitrap instruments MS and MS/MS 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, as well as a detailed step-by-step tutorial, please refer to the supplementary material of the 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 PXD000513. Publication: @article{kramer2014photo, title={Photo-cross-linking and high-resolution mass spectrometry for assignment of RNA-binding sites in RNA-binding proteins}, author={Kramer, Katharina and Sachsenberg, Timo and Beckmann, Benedikt M and Qamar, Saadia and Boon, Kum-Loong and Hentze, Matthias W and Kohlbacher, Oliver and Urlaub, Henning}, journal={Nature methods}, volume={11}, number={10}, pages={1064–1070}, year={2014}, publisher={Nature Publishing Group} } FAQ: Q: RNPxlcrashes with error message indicating that an idXML was not found: Error: File not found (the file ‘C:/Users/username/AppData/Local/Temp/MSfilename_Number_Number_variant.idXML’ could not be found) RNPxl failed! A: OMSSA has problems reading the path to the database. Check that the path to your database or windows temp directory doesn’t contain any spaces or additional dots. Make sure that all database related files (.fasta, .phr, .pin, .psq) are in the same folder and have the same name that you defined both in the parameters of the RNPxl tool and the OMSSA .ini file. Also make sure there is no dot except for the one between file name and file type, e.g., do not call the database “uniprot.human.fasta” Q: Can you provide some details on the mass and losses of 4-thio-U nucleotide? A: The monoisotopic mass of a 4-thio-U nucleotide is: 340.01301 (C9H13N2O8PS).However, a net loss of H2S has always been observed in our cross-linking experiments, making the adduct mass: 306.02529 (C9H11N2O8P). This adduct is observed on precursor level. Fragmentation cleaves off phosphate and ribose, leaving 94.01671 (C4H2N2O) as adduct on MS2 level. If you are interested in the original data, binaries and workflows you may download: […]
MetaProSIP: automated inference of elemental fluxes in microbial communities Note: MetaProSIP has been fully integrated into OpenMS. No additional installer is required anymore. Update: MetaProSIP now supports labeling experiments with heavy water (D, 18O) Download an updated KNIME workflow: here Advanced workflow including mass recalibration, alignment, and ID pooling: here 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 MetaProSIP publication. Publications: MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics @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 a non-zero 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 your PATH environment variable. Q: What do the columns in the group output refer to A: See this annotated example sheet […]