Crux: Rapid Open Source Protein Tandem Mass Spectrometry Analysis

McIlwain, Sean J.; Tamura, Kaipo; Kertész‐Farkas, Attila; Grant, Charles E.; Diament, Benjamin J.; Frewen, Barbara; Howbert, James Jeffry; Hoopmann, Michael R.; Käll, Lukas; Eng, Jimmy K.; MacCoss, Michael J.; Noble, William Stafford

doi:10.1021/pr500741y

Cited by 139 publications

(136 citation statements)

References 22 publications

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“…This database was combined with the UniProt SwissProt and trEMBL databases. The CRUX (McIlwain et al, 2014) mass spectrometry analysis toolkit was used to perform all subsequent searching, ranking and quantification of proteins and peptides and to construct a decoy database of peptides to empirically calculate a false discovery rate. The decoy database was constructed using the CRUX amino acid permutation method.…”

Section: Methodsmentioning

confidence: 99%

Widespread Accumulation of Ribosome-Associated Isolated 3′ UTRs in Neuronal Cell Populations of the Aging Brain

et al. 2018

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SUMMARY Particular brain regions and cell populations exhibit increased susceptibility to aging-related stresses. Here, we describe the age-specific and brain-region-specific accumulation of ribosome-associated 3′ UTR RNAs that lack the 5′ UTR and open reading frame. Our study reveals that this phenomenon impacts hundreds of genes in aged D1 spiny projection neurons of the mouse striatum and also occurs in the aging human brain. Isolated 3′ UTR accumulation is tightly correlated with mitochondrial gene expression and oxidative stress, with full-length mRNA expression that is reduced but not eliminated, and with production of short 3′ UTR-encoded peptides. Depletion of the oxidation-sensitive Fe-S cluster ribosome recycling factor ABCE1 induces the accumulation of 3′ UTRs, consistent with a model in which ribosome stalling and mRNA cleavage by No-Go decay yields isolated 3′ UTR RNAs protected by ribosomes. Isolated 3′ UTR accumulation is a hallmark of brain aging, likely reflecting regional differences in metabolism and oxidative stress.

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Section: Methodsmentioning

confidence: 99%

Widespread Accumulation of Ribosome-Associated Isolated 3′ UTRs in Neuronal Cell Populations of the Aging Brain

et al. 2018

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“…The following search engines and postsearch validation tools were used in the evaluation: X!⁠Tandem (v. 2012.10.01), IdentiPy (v. 0.2), MSGF+ (v. 2018.01.30), MSFragger (v. 20170103.0), Comet (v. 2016.01 rev. 1) from Crux (v. 3.1), Q‐ranker from Crux, Percolator from Crux, Percolator standalone (v. 3.01), MP score, PeptideProphet from Philosopher (https://github.com/prvst/philosopher), and ProteinProphet from Philosopher.…”

Section: Resultsmentioning

confidence: 99%

Scavager: A Versatile Postsearch Validation Algorithm for Shotgun Proteomics Based on Gradient Boosting

et al. 2018

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Shotgun proteomics workflows for database protein identification typically include a combination of search engines and postsearch validation software based mostly on machine learning algorithms. Here, a new postsearch validation tool called Scavager employing CatBoost, an open‐source gradient boosting library, which shows improved efficiency compared with the other popular algorithms, such as Percolator, PeptideProphet, and Q‐ranker, is presented. The comparison is done using multiple data sets and search engines, including MSGF+, MSFragger, X!Tandem, Comet, and recently introduced IdentiPy. Implemented in Python programming language, Scavager is open‐source and freely available at https://bitbucket.org/markmipt/scavager.

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“…25 Both types of scores were collected using tide-search with flanking peaks not allowed. X!Tandem version 2013.09.01.1 was used, with PSMs scored by E-value.…”

Section: Methodsmentioning

confidence: 99%

Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass Spectra

2016

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A central problem in mass spectrometry analysis involves identifying, for each observed tandem mass spectrum, the corresponding generating peptide. We present a dynamic Bayesian network (DBN) toolkit that addresses this problem by using a machine learning approach. At the heart of this toolkit is a DBN for Rapid Identification (DRIP), which can be trained from collections of high-confidence peptide-spectrum matches (PSMs). DRIP’s score function considers fragment ion matches using Gaussians rather than fixed fragment-ion tolerances and also considers all possible alignments between the theoretical and observed spectrum to find the optimal such alignment. This function not only yields state-of-the art database search accuracy but also can be used to generate features that significantly boost the performance of the Percolator post-processor. The DRIP software is built upon a general purpose DBN toolkit (GMTK), thereby allowing a wide variety of options for user-specific inference tasks, as well as facilitating easy modifications to the DRIP model in future work. DRIP is implemented in Python and C++, and is available under Apache license at http://melodi-lab.github.io/dripToolkit.

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Crux: Rapid Open Source Protein Tandem Mass Spectrometry Analysis

Cited by 139 publications

References 22 publications

Widespread Accumulation of Ribosome-Associated Isolated 3′ UTRs in Neuronal Cell Populations of the Aging Brain

Widespread Accumulation of Ribosome-Associated Isolated 3′ UTRs in Neuronal Cell Populations of the Aging Brain

Scavager: A Versatile Postsearch Validation Algorithm for Shotgun Proteomics Based on Gradient Boosting

Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass Spectra

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