Literature DB >> 30523686

DeltaMass: Automated Detection and Visualization of Mass Shifts in Proteomic Open-Search Results.

Dmitry M Avtonomov1, Andy Kong1, Alexey I Nesvizhskii1,2.   

Abstract

Routine identification of thousands of proteins in a single LC-MS experiment has long become the norm. With these vast amounts of data, more rigorous treatment of modified forms of peptides becomes possible. "Open search", a protein database search with a large precursor ion mass tolerance window, is becoming a popular method to evaluate possible sets of post-translational and chemical modifications in samples. The extraction of statistical information about the modification from peptide search results requires additional effort and data processing, such as recalibration of masses and accurate detection of precursors in MS1 signals. Here we present a software tool, DeltaMass, which performs kernel-density-based estimation of observed mass shifts and allows for the detection of poorly resolved mass deltas. The software also maps observed mass shifts to known modifications from public databases such as UniMod and augments them with additionally generated possible chemical changes to the molecule. Its interactive graphical interface provides an effective option for the visual interrogation of the data and the identification of potentially interesting mass shifts or unusual artifacts for subsequent analysis. However, the program can also be used in fully automated command-line mode to generate mass-shift peak lists as well.

Entities:  

Keywords:  GUI; chemical modification; data visualization; kernel density; mass shift; open search; peak detection; post-translational modification; proteomics

Mesh:

Year:  2018        PMID: 30523686      PMCID: PMC8864583          DOI: 10.1021/acs.jproteome.8b00728

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  19 in total

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3.  The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.

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4.  The PSI-MOD community standard for representation of protein modification data.

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5.  Enhanced Global Post-translational Modification Discovery with MetaMorpheus.

Authors:  Stefan K Solntsev; Michael R Shortreed; Brian L Frey; Lloyd M Smith
Journal:  J Proteome Res       Date:  2018-04-02       Impact factor: 4.466

6.  De novo peptide sequencing by deep learning.

Authors:  Ngoc Hieu Tran; Xianglilan Zhang; Lei Xin; Baozhen Shan; Ming Li
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-18       Impact factor: 11.205

7.  PEAKS DB: de novo sequencing assisted database search for sensitive and accurate peptide identification.

Authors:  Jing Zhang; Lei Xin; Baozhen Shan; Weiwu Chen; Mingjie Xie; Denis Yuen; Weiming Zhang; Zefeng Zhang; Gilles A Lajoie; Bin Ma
Journal:  Mol Cell Proteomics       Date:  2011-12-20       Impact factor: 5.911

8.  A mass-tolerant database search identifies a large proportion of unassigned spectra in shotgun proteomics as modified peptides.

Authors:  Joel M Chick; Deepak Kolippakkam; David P Nusinow; Bo Zhai; Ramin Rad; Edward L Huttlin; Steven P Gygi
Journal:  Nat Biotechnol       Date:  2015-06-15       Impact factor: 54.908

9.  MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics.

Authors:  Andy T Kong; Felipe V Leprevost; Dmitry M Avtonomov; Dattatreya Mellacheruvu; Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2017-04-10       Impact factor: 28.547

10.  ProSight PTM 2.0: improved protein identification and characterization for top down mass spectrometry.

Authors:  Leonid Zamdborg; Richard D LeDuc; Kevin J Glowacz; Yong-Bin Kim; Vinayak Viswanathan; Ian T Spaulding; Bryan P Early; Eric J Bluhm; Shannee Babai; Neil L Kelleher
Journal:  Nucleic Acids Res       Date:  2007-06-22       Impact factor: 16.971

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  4 in total

1.  Crystal-C: A Computational Tool for Refinement of Open Search Results.

Authors:  Hui-Yin Chang; Andy T Kong; Felipe da Veiga Leprevost; Dmitry M Avtonomov; Sarah E Haynes; Alexey I Nesvizhskii
Journal:  J Proteome Res       Date:  2020-05-08       Impact factor: 4.466

2.  Open Database Searching Enables the Identification and Comparison of Bacterial Glycoproteomes without Defining Glycan Compositions Prior to Searching.

Authors:  Ameera Raudah Ahmad Izaham; Nichollas E Scott
Journal:  Mol Cell Proteomics       Date:  2020-06-23       Impact factor: 5.911

3.  Extremely Fast and Accurate Open Modification Spectral Library Searching of High-Resolution Mass Spectra Using Feature Hashing and Graphics Processing Units.

Authors:  Wout Bittremieux; Kris Laukens; William Stafford Noble
Journal:  J Proteome Res       Date:  2019-08-30       Impact factor: 4.466

4.  α-Methylene-β-Lactone Scaffold for Developing Chemical Probes at the Two Ends of the Selectivity Spectrum.

Authors:  Lei Wang; Louis P Riel; Bekim Bajrami; Bin Deng; Amy R Howell; Xudong Yao
Journal:  Chembiochem       Date:  2020-11-11       Impact factor: 3.164

  4 in total

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