TOPP(1)

✨ TOPP(1) · General Commands Manual 🦋 (part 1 of 2)

🌸 NAME 🌸

okay so the name is topp, which is a library for LC/MS data management and analysis, plus its tools 🧚

💅 DESCRIPTION 💅

bestie, this page is a quick intro to the topp package 💖 It's a set of binary tools that help you build the OpenMS proteomics pipeline (topp) 🔥

OpenMS gives you the infrastructure to develop mass spectrometry software, plus powerful 2D and 3D visualization solutions ✨ It's giving whole toolkit energy 👑

It also covers analyses for a bunch of quantitation protocols: label-free quantitation, SILAC, iTRAQ, SRM, SWATH… 📊

It has built-in algorithms for de-novo identification and database search 🧠 Plus adapters for other state-of-the-art tools like X!Tandem, Mascot, and OMSSA 🤝

And it supports the Proteomics Standard Initiative (PSI) formats for MS data 🎀 Tools slot right into workflow engines like Knime, Galaxy, WS-Pgrade, and TOPPAS through the TOPPtools concept, with unified parameter handling 🦋 literally so easy, no cap 💅

🦋 AVAILABLE MODULES 🦋

here's the whole lineup, main character list incoming 💅

• AccurateMassSearch — matches MS signals to molecules in a database by mass 🎯
• AssayGeneratorMetabo — generates assay libraries from DDA data (Metabolomics) 🧪
• BaselineFilter — removes the baseline from profile spectra with a top-hat filter 🧹
• CVInspector — a tool for visualizing and validating PSI mapping and CV files 👀
• ClusterMassTraces — creates pseudo spectra ✨
• ClusterMassTracesByPrecursor — correlates precursor masstraces with fragment ion masstraces in SWATH maps based on their elution profile 🌊
• CometAdapter — annotates MS/MS spectra using Comet 💬
• CompNovo — performs de novo peptide identification using the CompNovo engine 🧠
• CompNovoCID — performs de novo peptide identification using the CompNovo engine 💜
• ConsensusID — computes a consensus of peptide identifications from several identification engines 🤝
• ConsensusMapNormalizer — normalizes maps of one consensusXML file 📏
• CruxAdapter — identifies MS/MS spectra using Crux 🔎
• DTAExtractor — extracts spectra from an MS run file into several files in DTA format 📂
• DatabaseFilter — filters a protein database (FASTA format) based on identified proteins 🧹
• DatabaseSuitability — computes a suitability score for a database used in a peptide identification search, and also reports the quality of LC-MS spectra 📊
• DeMeanderize — orders the spectra of MALDI spotting plates correctly 🗂️
• Decharger — decharges and merges different feature charge variants of the same peptide 🔋
• DecoyDatabase — creates a decoy sequence database from a forward sequence database 🎭
• Digestor — digests a protein database in-silico 🍽️
• DigestorMotif — digests a protein database in-silico 🥄
• EICExtractor — extracts intensities from dedicated positions in an LC/MS map 📍
• ERPairFinder — a util for evaluating pair ratios on enhanced resolution (zoom) scans 🔬
• Epifany — runs a Bayesian protein inference 🧮
• ExecutePipeline — executes workflows created by TOPPAS ▶️
• ExternalCalibration — applies an external mass recalibration ⚖️
• FFEval — an evaluation tool for feature detection algorithms 📝
• FalseDiscoveryRate — estimates the false discovery rate on peptide and protein level using decoy searches 🚨
• FeatureFinderCentroided — detects two-dimensional features in LC-MS data 🔍
• FeatureFinderIdentification — detects features in MS1 data based on peptide identifications 🪪
• FeatureFinderIsotopeWavelet — detects two-dimensional features in LC-MS data 🌊
• FeatureFinderMRM — detects two-dimensional features in LC-MS data 🎯
• FeatureFinderMetabo — assembles metabolite features from centroided (LC-)MS data using the mass trace approach 🧵
• FeatureFinderMetaboIdent — detects features in MS1 data based on metabolite identifications 💎
• FeatureFinderMultiplex — determines peak ratios in LC-MS data ⚖️
• FeatureFinderSuperHirn — finds mass spectrometric features in mass spectra 🦸
• FeatureLinkerLabeled — groups corresponding isotope-labeled features in a feature map 🔗
• FeatureLinkerUnlabeled — groups corresponding features from multiple maps 🔗
• FeatureLinkerUnlabeledKD — groups corresponding features from multiple maps 🔗
• FeatureLinkerUnlabeledQT — groups corresponding features from multiple maps 🔗
• FidoAdapter — runs the protein inference engine Fido 🐶
• FileConverter — converts between different MS file formats 🔄
• FileFilter — extracts or manipulates portions of data from peak, feature, or consensus-feature files ✂️
• FileInfo — shows basic information about a file, like data ranges and file type ℹ️
• FileMerger — merges several MS files into one file 🫂
• FuzzyDiff — compares two files while tolerating numeric differences 🌫️
• GNPSExport — a tool that exports consensus features into MGF format 📤
• GenericWrapper — allows generic wrapping of external tools 🎁
• HighResPrecursorMassCorrector — corrects the precursor mass and charge determined by the instrument software 🛠️
• IDConflictResolver — resolves ambiguous annotations of features with peptide identifications 🤼
• IDDecoyProbability — estimates peptide probabilities using a decoy search strategy 🎲
• IDExtractor — extracts 'n' peptides randomly or the best 'n' from idXML files 🎰
• IDFileConverter — converts identification engine file formats 🔁
• IDFilter — filters results from protein or peptide identification engines based on different criteria 🚰
• IDMapper — assigns protein/peptide identifications to features or consensus features 📌
• IDMassAccuracy — calculates a distribution of the mass error from given mass spectra and IDs 📐
• IDMerger — merges several protein/peptide identification files into one file 🧩
• IDPosteriorErrorProbability — estimates probabilities for incorrectly assigned peptide sequences and a set of search engine scores using a mixture model 🧪
• IDRTCalibration — can be used to calibrate RTs of peptide hits linearly to standards ⏱️
• IDRipper — splits a protein/peptide identification file into several files according to annotated file origin 🪓
• IDScoreSwitcher — switches between different scores of peptide or protein hits in identification data 🔀
• IDSplitter — splits protein/peptide identifications off of annotated data files ✂️
• INIFileEditor — an editor for OpenMS configuration files 📝
• INIUpdater — updates INI and TOPPAS files to a new OpenMS version ⬆️
• ImageCreator — transforms an LC-MS map into an image 🖼️
• InclusionExclusionListCreator — creates inclusion and/or exclusion lists 📋
• InspectAdapter — annotates MS/MS spectra using Inspect 🕵️
• InternalCalibration — applies an internal mass recalibration ⚖️
• IsobaricAnalyzer — calculates isobaric quantitative values for peptides 🌈
• LabeledEval — an evaluation tool for isotope-labeled quantitation experiments 📊
• LuciphorAdapter — modification site localisation using LuciPHOr2 📍

⏭️ the rest of the modules, starting with MRMMapper, are coming up in part 2 👀

• PTPredict — okay so this one predicts how likely peptides are to be proteotypic 🧬, using an svm_model that was trained by PTModel 💜
• PeakPickerHiRes — finds mass spectrometric peaks in profile mass spectra ✨
• PeakPickerIterative — also finds mass spectrometric peaks in profile mass spectra, same vibe as the one above 🌸
• PeakPickerWavelet — yep, you guessed it, it finds mass spectrometric peaks in profile mass spectra 🦋
• PepNovoAdapter — an adapter for PepNovo that supports every PepNovo command line parameter 🔥 It converts the PepNovo text outfile format into the idXML format, which is so useful 💅
• PeptideIndexer — refreshes the protein references for all peptide hits 🫶
• PercolatorAdapter — helps you feed input into Percolator and reintegrate the results 🌈
• PhosphoScoring — scores potential phosphorylation sites so you can localize the most probable ones 💖
• PrecursorIonSelector — honestly the description is just its own name 🙈 no extra tea here
• PrecursorMassCorrector — corrects the precursor entries of MS/MS spectra by using MS1 information 🍓
• ProteinInference — does protein inference based on an aggregation of the scores of the identified peptides 👑
• ProteinQuantifier — computes peptide and protein abundances 💜
• ProteinResolver — protein inference, but make it a different tool ⭐
• ProteomicsLFQ — a standard proteomics LFQ pipeline, very main character energy 🎀
• QCCalculator — calculates basic quality parameters from MS experiments and their analysis data, like identification or feature detection 📊
• QCEmbedder — attaches a table or an image to a given qc parameter 🖼️
• QCExporter — pulls several qp from several run/sets and exports them in a tabular format 🦋
• QCExtractor — extracts a table attachment for a given qc parameter 🧚
• QCImporter — imports tables with quality control parameters into qcml files 💅
• QCMerger — merges two qcml files together 🫶
• QCShrinker — removes the verbose table attachments from a qcml file that you don't need anymore, like for a final report 🧹
• QualityControl — computes a bunch of QC metrics from many possible input files, but only the consensusXML is required 💖 The more optional files you give it, the more metrics you get, so feed it everything 🔥
• RNADigestor — digests an RNA sequence database in-silico 🧬
• RNAMassCalculator — calculates masses, mass-to-charge ratios and sum formulas of RNA sequences 🌙
• RNPxlSearch — annotates RNA/DNA-peptide cross-links in MS/MS spectra 🕸️
• RNPxlXICFilter — removes MS2 spectra from treatment based on the fold change between control and treatment 🍓
• RTEvaluation — evaluates TPs (true positives), TNs, FPs, and FNs for an idXML file with predicted RTs ✅
• RTModel — trains a model for retention time prediction of peptides from a training set 🎓
• RTPredict — predicts retention times for peptides using a model trained by RTModel ⏱️
• Resampler — transforms an LC/MS map into a resampled map or a PNG image 🌸
• SeedListGenerator — generates seed lists for feature detection 🌱
• SemanticValidator — semantically validates certain XML files 💅
• SequenceCoverageCalculator — prints information about idXML files 📜
• SimpleSearchEngine — annotates MS/MS spectra using SimpleSearchEngine 🔍
• SiriusAdapter — a tool for metabolite identification using single and tandem mass spectrometry 🧪
• SpecLibCreator — creates an MSP formatted spectral library 📚
• SpecLibSearcher — identifies peptide MS/MS spectra by spectral matching against a searchable spectral library 🔎
• SpectraFilterBernNorm — applies thresholdfilter to peak spectra 💧
• SpectraFilterMarkerMower — applies thresholdfilter to peak spectra 💧
• SpectraFilterNLargest — applies thresholdfilter to peak spectra 💧
• SpectraFilterNormalizer — normalizes intensity of peak spectra ⚖️
• SpectraFilterParentPeakMower — applies thresholdfilter to peak spectra 💧
• SpectraFilterScaler — applies thresholdfilter to peak spectra 💧
• SpectraFilterSqrtMower — applies thresholdfilter to peak spectra 💧
• SpectraFilterThresholdMower — applies thresholdfilter to peak spectra 💧
• SpectraFilterWindowMower — applies thresholdfilter to peak spectra 💧
• SpectraMerger — merges spectra (each MS level separately) to boost S/N ratios 📈
• SpectraSTSearchAdapter — an interface to the SEARCH Mode of the SpectraST executable 🔌
• StaticModification — applies a set of modifications to all PeptideIDs in an idXML file 🎨
• SvmTheoreticalSpectrumGeneratorTrainer — trains SVM models to be used as input for SvmTheoreticalSpectrumGenerator 🧠
• SwathWizard — an assistant for Swath-Analysis 🧙
• TICCalculator — calculates the TIC from a mass spectrometric raw file, useful for benchmarking 🏁
• TOFCalibration — applies time of flight calibration ⏲️
• TOPPAS — an assistant for GUI-driven TOPP workflow design 🖱️
• TOPPView — a viewer for mass spectrometry data 👀
• TargetedFileConverter — converts different transition files for targeted proteomics/metabolomics analysis 🔁
• TextExporter — exports various XML formats to a text file 📝
• TransformationEvaluation — applies a transformation to a range of values 🧮
• XFDR — calculates false discovery rate estimates on crosslink identifications 🎯
• XMLValidator — validates XML files against an XSD schema ✔️
• XTandemAdapter — annotates MS/MS spectra using X! Tandem 🧬

✨ BIBLIOGRAPHICAL REFERENCE TO BE CITED ✨

Marc Sturm, Andreas Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Alexandra Zerck, Knut Reinert, and Oliver Kohlbacher (2008) OpenMS – an Open-Source Software Framework for Mass Spectrometry. BMC Bioinformatics, 9:163. doi:10.1186/1471-2105-9-163. 📖 Please cite this one, bestie, it's the iconic paper 🫶

✨ SEE ALSO ✨

libopenms(3), openms-common(7), openms(7), openms-doc(7).

The program is documented fully in the Tutorials, which are packaged in openms-doc 📚 go check those out, they're so helpful 🥹

✨ AUTHOR ✨

This manual page was written by Filippo Rusconi <lopippo@debian.org> 💜 Permission is granted to copy, distribute and/or modify this document under the terms of the GNU General Public License, Version 3, published by the Free Software Foundation.

On a Debian system, the complete text of the GNU General Public License version 3 can be found in the file /usr/share/common-licenses/GPL-3 📜

Okay that's the whole page, bestie 💖 Last updated November 2012 for TOPP(1) 🌸 Stay iconic and keep those peaks picked ✨🦋