OMSSA Parser: An open‐source library to parse and extract data from OMSSA MS/MS search results

Protein identification by MS is an important technique in both gel‐based and gel‐free proteome studies. The Open Mass Spectrometry Search Algorithm (OMSSA) ( http://pubchem.ncbi.nlm.nih.gov/omssa ) is an open‐source search engine that can be used to identify MS/MS spectra acquired in these experiments. We here present a lightweight, open‐source Java software library, OMSSA Parser ( http://code.google.com/p/omssa‐parser ), which parses OMSSA omx result files into easy accessible and fully functional object models. In addition, we also provide examples illustrating the usage of our library.     

SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches

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.     

Comet: An open‐source MS/MS sequence database search tool

Proteomics research routinely involves identifying peptides and proteins via MS/MS sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open‐source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years.     

IPeak: An open source tool to combine results from multiple MS/MS search engines

Liquid chromatography coupled tandem mass spectrometry (LC‐MS/MS) is an important technique for detecting peptides in proteomics studies. Here, we present an open source software tool, termed IPeak, a peptide identification pipeline that is designed to combine the Percolator post‐processing algorithm and multi‐search strategy to enhance the sensitivity of peptide identifications without compromising accuracy. IPeak provides a graphical user interface (GUI) as well as a command‐line interface, which is implemented in JAVA and can work on all three major operating system platforms: Windows, Linux/Unix and OS X. IPeak has been designed to work with the mzIdentML standard from the Proteomics Standards Initiative (PSI) as an input and output, and also been fully integrated into the associated mzidLibrary project, providing access to the overall pipeline, as well as modules for calling Percolator on individual search engine result files. The integration thus enables IPeak (and Percolator) to be used in conjunction with any software packages implementing the mzIdentML data standard. IPeak is freely available and can be downloaded under an Apache 2.0 license at https://code.google.com/p/mzidentml‐lib/ .     

FragmentationAnalyzer: An open‐source tool to analyze MS/MS fragmentation data

A thorough understanding of the fragmentation processes in MS/MS can be a powerful tool in assessing the resulting peptide and protein identifications. We here present the freely available, open‐source FragmentationAnalyzer tool ( http://fragmentation‐analyzer.googlecode.com ) that makes it straightforward to analyze large MS/MS data sets for specific types of identified peptides, using a common set of peptide properties. This enables the detection of fragmentation pattern nuances related to specific instruments or due to the presence of post‐translational modifications.     

OMSSAGUI: An open-source user interface component to configure and run the OMSSA search engine

We here present a user-friendly and extremely lightweight tool that can serve as a stand-alone front-end for the Open MS Search Algorithm (OMSSA) search engine, or that can directly be used as part of an informatics processing pipeline for MS driven proteomics. The OMSSA graphical user interface (OMSSAGUI) tool is written in Java, and is supported on Windows, Linux, and OSX platforms. It is an open source under the Apache 2 license and can be downloaded from http://code.google.com/p/mass-spec-gui/.     

STEPS: A grid search methodology for optimized peptide identification filtering of MS/MS database search results

For bottom‐up proteomics, there are wide variety of database‐searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid‐search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection‐–referred to as STEPS‐–utilizes user‐defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal “parameter set” for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true‐positive identifications are demonstrated using datasets derived from immunoaffinity‐depleted blood serum and a bacterial cell lysate, two common proteomics sample types.     

MassSieve: Panning MS/MS peptide data for proteins

We present MassSieve, a Java‐based platform for visualization and parsimony analysis of single and comparative LC‐MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC‐MS/MS‐based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments.     

GradientOptimizer: An open‐source graphical environment for calculating optimized gradients in reversed‐phase liquid chromatography

We here present GradientOptimizer, an intuitive, lightweight graphical user interface to design nonlinear gradients for separation of peptides by reversed‐phase liquid chromatography. The software allows to calculate three types of nonlinear gradients, each of them optimizing a certain retention time distribution of interest. GradientOptimizer is straightforward to use, requires minimum processing of the input files, and is supported under Windows, Linux, and OS X platforms. The software is open‐source and can be downloaded under an Apache 2.0 license at https://github.com/statisticalbiotechnology/NonlinearGradientsUI .     

pepgrep: A Tool for Peptide MS/MS Pattern Matching

Typically, detection of protein sequences in collision-induced dissociation (CID) tandem MS (MS2) dataset is performed by mapping identified peptide ions back to protein sequence by using the protein database search (PDS) engine. Finding a particular peptide sequence of interest in CID MS2 records very often requires manual evaluation of the spectrum, regardless of whether the peptide-associated MS2 scan is identified by PDS algorithm or not. We have developed a compact cross-platform database-free command-line utility, pepgrep, which helps to find an MS2 fingerprint for a selected peptide sequence by pattern-matching of modelled MS2 data using Peptide-to-MS2 scoring algorithm. pepgrep can incorporate dozens of mass offsets corresponding to a variety of post-translational modifications (PTMs) into the algorithm. Decoy peptide sequences are used with the tested peptide sequence to reduce false-positive results. The engine is capable of screening an MS2 data file at a high rate when using a cluster computing environment. The matched MS2 spectrum can be displayed by using built-in graphical application programming interface (API) or optionally recorded to file. Using this algorithm, we were able to find extra peptide sequences in studied CID spectra that were missed by PDS identification. Also we found pepgrep especially useful for examining a CID of small fractions of peptides resulting from, for example, affinity purification techniques. The peptide sequences in such samples are less likely to be positively identified by using routine protein-centric algorithm implemented in PDS. The software is freely available at http://bsproteomics.essex.ac.uk:8080/data/download/pepgrep-1.4.tgz.     

A simple workflow to increase MS2 identification rate by subsequent spectral library search

Searching a spectral library for the identification of protein MS/MS data has proven to be a fast and accurate method, while yielding a high identification rate. We investigated the potential to increase peptide discovery rate, with little increase in computational time, by constructing a workflow based on a sequence search with Phenyx followed by a library search with SpectraST. Searching a consensus library compiled from the search results of the prior Phenyx search increased the number of confidently matched spectra by up to 156%. Additionally matched spectra by SpectraST included noisy spectra, spectra representing missed cleaved peptides as well as spectra from post‐translationally modified peptides.     

jmzML,an open‐source Java API for mzML,the PSI standard for MS data

We here present jmzML, a Java API for the Proteomics Standards Initiative mzML data standard. Based on the Java Architecture for XML Binding and XPath‐based XML indexer random‐access XML parser, jmzML can handle arbitrarily large files in minimal memory, allowing easy and efficient processing of mzML files using the Java programming language. jmzML also automatically resolves internal XML references on‐the‐fly. The library (which includes a viewer) can be downloaded from http://jmzml.googlecode.com .     

The OMSSAPercolator: An automated tool to validate OMSSA results

Protein identification by MS/MS is an important technique in proteome studies. The Open Mass Spectrometry Search Algorithm (OMSSA) is an open‐source search engine that can be used to identify MS/MS spectra acquired in these experiments. Here, we present a software tool, termed OMSSAPercolator, which interfaces OMSSA with Percolator, a post‐search machine learning method for rescoring database search results. We demonstrate that it outperforms the standard OMSSA scoring scheme, and provides reliable significant measurements. OMSSAPercolator is programmed using JAVA and can be readily used as a standalone tool or integrated into existing data analysis pipelines. OMSSAPercolator is freely available and can be downloaded at http://sourceforge.net/projects/omssapercolator/ .     

OVNIp: An open source application facilitating the interpretation,the validation and the edition of proteomics data generated by MS analyses and de novo sequencing

Several academic software are available to help the validation and reporting of proteomics data generated by MS analyses. However, to our knowledge, none of them have been conceived to meet the particular needs generated by the study of organisms whose genomes are not sequenced. In that context, we have developed OVNIp, an open‐source application which facilitates the whole process of proteomics results interpretation. One of its unique attributes is its capacity to compile multiple results (from several search engines and/or several databank searches) with a resolution of conflicting interpretations. Moreover, OVNIp enables automated exploitation of de novo sequences generated from unassigned MS/MS spectra leading to higher sequence coverage and enhancing confidence in the identified proteins. The exploitation of these additional spectra might also identify novel proteins through a MS‐BLAST search, which can be easily ran from the OVNIp interface. Beyond this primary scope, OVNIp can also benefit to users who look for a simple standalone application to both visualize and confirm MS/MS result interpretations through a simple graphical interface and generate reports according to user‐defined forms which may integrate the prerequisites for publication. Sources, documentation and a stable release for Windows are available at http://wwwappli.nantes.inra.fr:8180/OVNIp .     

An improved workflow for identifying ubiquitin/ubiquitin‐like protein conjugation sites from tandem mass spectra

The identification of ubiquitin (Ub) and Ub‐like protein (Ubl) conjugation sites is important in understanding their roles in biological pathway regulations. However, unambiguously and sensitively identifying Ub/Ubl conjugation sites through high‐throughput MS remains challenging. We introduce an improved workflow for identifying Ub/Ubl conjugation sites based on the ChopNSpice and X!Tandem software. ChopNSpice is modified to generate Ub/Ubl conjugation peptides in the form of a cross‐link. A combinatorial FASTA database can be acquired using the modified ChopNSpice (MchopNSpice). The modified X!Tandem (UblSearch) introduces a new fragmentation model for the Ub/Ubl conjugation peptides to match unambiguously the MS/MS spectra with linear peptides or Ub/Ubl conjugation peptides using the combinatorial FASTA database. The novel workflow exhibited better performance in analyzing an Ub and Ubl spectral library and a large‐scale Trypanosoma cruzi small Ub‐related modifier dataset compared with the original ChopNSpice method. The proposed workflow is more suitable for processing large‐scale MS datasets of Ub/Ubl modification. MchopNSpice and UblSearch are freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/maublsearch .     

LFQuant: A label‐free fast quantitative analysis tool for high‐resolution LC‐MS/MS proteomics data

Database searching based methods for label‐free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross‐assignment among different runs. Here, we present a new label‐free fast quantitative analysis tool, LFQuant, for high‐resolution LC‐MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large‐scale label‐free data with fractionation such as SDS‐PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL‐Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/ .     

SwissPIT: An workflow‐based platform for analyzing tandem‐MS spectra using the Grid

The identification and characterization of peptides from MS/MS data represents a critical aspect of proteomics. It has been the subject of extensive research in bioinformatics resulting in the generation of a fair number of identification software tools. Most often, only one program with a specific and unvarying set of parameters is selected for identifying proteins. Hence, a significant proportion of the experimental spectra do not match the peptide sequences in the screened database due to inappropriate parameters or scoring schemes. The Swiss protein identification toolbox (swissPIT) project provides the scientific community with an expandable multitool platform for automated in‐depth analysis of MS data also able to handle data from high‐throughput experiments. With swissPIT many problems have been solved: The missing standards for input and output formats (A), creation of analysis workflows (B), unified result visualization (C), and simplicity of the user interface (D). Currently, swissPIT supports four different programs implementing two different search strategies to identify MS/MS spectra. Conceived to handle the calculation‐intensive needs of each of the programs, swissPIT uses the distributed resources of a Swiss‐wide computer Grid (http://www.swing‐grid.ch).     

landscapemetrics: an open‐source R tool to calculate landscape metrics

Quantifying landscape characteristics and linking them to ecological processes is one of the central goals of landscape ecology. Landscape metrics are a widely used tool for the analysis of patch‐based, discrete land‐cover classes. Existing software to calculate landscape metrics has several constraints, such as being limited to a single platform, not being open‐source or involving a complicated integration into large workflows. We present landscapemetrics, an open‐source R package that overcomes many constraints of existing landscape metric software. The package includes an extensive collection of commonly used landscape metrics in a tidy workflow. To facilitate the integration into large workflows, landscapemetrics is based on a well‐established spatial framework in R. This allows pre‐processing of land‐cover maps or further statistical analysis without importing and exporting the data from and to different software environments. Additionally, the package provides many utility functions to visualize, extract, and sample landscape metrics. Lastly, we provide building‐blocks to motivate the development and integration of new metrics in the future. We demonstrate the usage and advantages of landscapemetrics by analysing the influence of different sampling schemes on the estimation of landscape metrics. In so doing, we demonstrate the many advantages of the package, especially its easy integration into large workflows. These new developments should help with the integration of landscape analysis in ecological research, given that ecologists are increasingly using R for the statistical analysis, modelling and visualization of spatial data.     

MS2‐Deisotoper: A Tool for Deisotoping High‐Resolution MS/MS Spectra in Normal and Heavy Isotope‐Labelled Samples

High‐resolution MS/MS spectra of peptides can be deisotoped to identify monoisotopic masses of peptide fragments. The use of such masses should improve protein identification rates. However, deisotoping is not universally used and its benefits have not been fully explored. Here, MS2‐Deisotoper, a tool for use prior to database search, is used to identify monoisotopic peaks in centroided MS/MS spectra. MS2‐Deisotoper works by comparing the mass and relative intensity of each peptide fragment peak to every other peak of greater mass, and by applying a set of rules concerning mass and intensity differences. After comprehensive parameter optimization, it is shown that MS2‐Deisotoper can improve the number of peptide spectrum matches (PSMs) identified by up to 8.2% and proteins by up to 2.8%. It is effective with SILAC and non‐SILAC MS/MS data. The identification of unique peptide sequences is also improved, increasing the number of human proteoforms by 3.7%. Detailed investigation of results shows that deisotoping increases Mascot ion scores, improves FDR estimation for PSMs, and leads to greater protein sequence coverage. At a peptide level, it is found that the efficacy of deisotoping is affected by peptide mass and charge. MS2‐Deisotoper can be used via a user interface or as a command‐line tool.