No abstract

The identification of proteins by mass spectrometry is a standard technique in the field of proteomics, relying on search engines to perform the identifications of the acquired spectra. Here, we present a user-friendly, lightweight and open-source graphical user interface called SearchGUI (http://searchgui.googlecode.com), for configuring and running the freely available OMSSA (open mass spectrometry search algorithm) and X!Tandem search engines simultaneously. Freely available under the permissible Apache2 license, SearchGUI is supported on Windows, Linux and OSX.

The Proteomics Identifications database (PRIDE, http://www.ebi.ac.uk/pride) at the European Bioinformatics Institute has become one of the main repositories of mass spectrometry-derived proteomics data. For the last 2 years, PRIDE data holdings have grown substantially, comprising 60 different species, more than 2.5 million protein identifications, 11.5 million peptides and over 50 million spectra by September 2009. We here describe several new and improved features in PRIDE, including the revised submission process, which now includes direct submission of fragment ion annotations. Correspondingly, it is now possible to visualize spectrum fragmentation annotations on tandem mass spectra, a key feature for compliance with journal data submission requirements. We also describe recent developments in the PRIDE BioMart interface, which now allows integrative queries that can join PRIDE data to a growing number of biological resources such as Reactome, Ensembl, InterPro and UniProt. This ability to perform extremely powerful across-domain queries will certainly be a cornerstone of future bioinformatics analyses. Finally, we highlight the importance of data sharing in the proteomics field, and the corresponding integration of PRIDE with other databases in the ProteomExchange consortium.

MotivationBioContainers (biocontainers.pro) is an open-source and community-driven framework which provides platform independent executable environments for bioinformatics software. BioContainers allows labs of all sizes to easily install bioinformatics software, maintain multiple versions of the same software and combine tools into powerful analysis pipelines. BioContainers is based on popular open-source projects Docker and rkt frameworks, that allow software to be installed and executed under an isolated and controlled environment. Also, it provides infrastructure and basic guidelines to create, manage and distribute bioinformatics containers with a special focus on omics technologies. These containers can be integrated into more comprehensive bioinformatics pipelines and different architectures (local desktop, cloud environments or HPC clusters).Availability and ImplementationThe software is freely available at github.com/BioContainers/.

In this study, the human cerebrospinal fluid (CSF) proteome was mapped using three different strategies prior to Orbitrap LC-MS/MS analysis: SDS-PAGE and mixed mode reversed phase-anion exchange for mapping the global CSF proteome, and hydrazide-based glycopeptide capture for mapping glycopeptides. A maximal protein set of 3081 proteins (28,811 peptide sequences) was identified, of which 520 were identified as glycoproteins from the glycopeptide enrichment strategy, including 1121 glycopeptides and their glycosylation sites. To our knowledge, this is the largest number of identified proteins and glycopeptides reported for CSF, including 417 glycosylation sites not previously reported. From parallel plasma samples, we identified 1050 proteins (9739 peptide sequences). An overlap of 877 proteins was found between the two body fluids, whereas 2204 proteins were identified only in CSF and 173 only in plasma. All mapping results are freely available via the new CSF Proteome Resource (http://probe.uib.no/csf-pr), which can be used to navigate the CSF proteome and help guide the selection of signature peptides in targeted quantitative proteomics.

Mass-spectrometry-based proteomics has become the standard approach for identifying and quantifying proteins. A vital step consists of analyzing experimentally generated mass spectra to identify the underlying peptide sequences for later mapping to the originating proteins. We here present the latest developments in SearchGUI, a common open-source interface for the most frequently used freely available proteomics search and de novo engines that has evolved into a central component in numerous bioinformatics workflows.

No abstract

The field of computational proteomics is approaching the big data age, driven both by a continuous growth in the number of samples analyzed per experiment as well as by the growing amount of data obtained in each analytical run. In order to process these large amounts of data, it is increasingly necessary to use elastic compute resources such as Linux-based cluster environments and cloud infrastructures. Unfortunately, the vast majority of cross-platform proteomics tools are not able to operate directly on the proprietary formats generated by the diverse mass spectrometers. Here, we present ThermoRawFileParser, an opensource, cross-platform tool that converts Thermo RAW files into open file formats such as MGF and the HUPO-PSI standard file format mzML. To ensure the broadest possible availability and to increase integration capabilities with popular workflow systems such as Galaxy or Nextflow, we have also built Conda package and BioContainers container around ThermoRawFileParser. In addition, we implemented a user-friendly interface (ThermoRawFileParserGUI) for those users not familiar with command-line tools. Finally, we performed a benchmark of ThermoRawFileParser and msconvert to verify that the converted mzML files contain reliable quantitative results.