Literature DB >> 29083185

Ultrafast Peptide Label-Free Quantification with FlashLFQ.

Robert J Millikin1, Stefan K Solntsev1, Michael R Shortreed1, Lloyd M Smith1,2.   

Abstract

The rapid and accurate quantification of peptides is a critical element of modern proteomics that has become increasingly challenging as proteomic data sets grow in size and complexity. We present here FlashLFQ, a computer program for high-speed label-free quantification of peptides following a search of bottom-up mass spectrometry data. FlashLFQ is approximately an order of magnitude faster than established label-free quantification methods. The increased speed makes it practical to base quantification upon all of the charge states for a given peptide rather than solely upon the charge state that was selected for MS2 fragmentation. This increases the number of quantified peptides, improves replicate-to-replicate reproducibility, and increases quantitative accuracy. We integrated FlashLFQ into the graphical user interface of the MetaMorpheus search software, allowing it to work together with the global post-translational modification discovery (G-PTM-D) engine to accurately quantify modified peptides. FlashLFQ is also available as a NuGet package, facilitating its integration into other software, and as a standalone command line software program for the quantification of search results from other programs (e.g., MaxQuant).

Entities:  

Keywords:  label-free quantification; post-translational modifications; quantitative proteomics; software

Mesh:

Substances:

Year:  2017        PMID: 29083185      PMCID: PMC5814109          DOI: 10.1021/acs.jproteome.7b00608

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


  18 in total

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Journal:  J Proteome Res       Date:  2004 Sep-Oct       Impact factor: 4.466

2.  Discovering known and unanticipated protein modifications using MS/MS database searching.

Authors:  Wilfred H Tang; Benjamin R Halpern; Ignat V Shilov; Sean L Seymour; Sean P Keating; Alex Loboda; Alpesh A Patel; Daniel A Schaeffer; Lydia M Nuwaysir
Journal:  Anal Chem       Date:  2005-07-01       Impact factor: 6.986

3.  moFF: a robust and automated approach to extract peptide ion intensities.

Authors:  Andrea Argentini; Ludger J E Goeminne; Kenneth Verheggen; Niels Hulstaert; An Staes; Lieven Clement; Lennart Martens
Journal:  Nat Methods       Date:  2016-11-29       Impact factor: 28.547

Review 4.  Tools for label-free peptide quantification.

Authors:  Sven Nahnsen; Chris Bielow; Knut Reinert; Oliver Kohlbacher
Journal:  Mol Cell Proteomics       Date:  2012-12-17       Impact factor: 5.911

5.  Proteoform: a single term describing protein complexity.

Authors:  Lloyd M Smith; Neil L Kelleher
Journal:  Nat Methods       Date:  2013-03       Impact factor: 28.547

6.  Quantitative proteomic analysis of microdissected breast cancer tissues: comparison of label-free and SILAC-based quantification with shotgun, directed, and targeted MS approaches.

Authors:  Ning Qing Liu; Lennard J M Dekker; Christoph Stingl; Coşkun Güzel; Tommaso De Marchi; John W M Martens; John A Foekens; Theo M Luider; Arzu Umar
Journal:  J Proteome Res       Date:  2013-09-13       Impact factor: 4.466

7.  An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts.

Authors:  Xiaomeng Shen; Shichen Shen; Jun Li; Qiang Hu; Lei Nie; Chengjian Tu; Xue Wang; Benjamin Orsburn; Jianmin Wang; Jun Qu
Journal:  J Proteome Res       Date:  2017-05-25       Impact factor: 4.466

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.  Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences.

Authors:  Bo Zhang; Mohammad Pirmoradian; Roman Zubarev; Lukas Käll
Journal:  Mol Cell Proteomics       Date:  2017-03-16       Impact factor: 5.911

10.  Global Post-Translational Modification Discovery.

Authors:  Qiyao Li; Michael R Shortreed; Craig D Wenger; Brian L Frey; Leah V Schaffer; Mark Scalf; Lloyd M Smith
Journal:  J Proteome Res       Date:  2017-03-01       Impact factor: 4.466

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  16 in total

1.  Identification of MS-Cleavable and Noncleavable Chemically Cross-Linked Peptides with MetaMorpheus.

Authors:  Lei Lu; Robert J Millikin; Stefan K Solntsev; Zach Rolfs; Mark Scalf; Michael R Shortreed; Lloyd M Smith
Journal:  J Proteome Res       Date:  2018-06-11       Impact factor: 4.466

2.  metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes.

Authors:  Caleb W Easterly; Ray Sajulga; Subina Mehta; James Johnson; Praveen Kumar; Shane Hubler; Bart Mesuere; Joel Rudney; Timothy J Griffin; Pratik D Jagtap
Journal:  Mol Cell Proteomics       Date:  2019-06-24       Impact factor: 5.911

3.  Bolt: a New Age Peptide Search Engine for Comprehensive MS/MS Sequencing Through Vast Protein Databases in Minutes.

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Journal:  J Am Soc Mass Spectrom       Date:  2019-08-26       Impact factor: 3.109

4.  A Bayesian Null Interval Hypothesis Test Controls False Discovery Rates and Improves Sensitivity in Label-Free Quantitative Proteomics.

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Journal:  J Proteome Res       Date:  2020-04-14       Impact factor: 4.466

5.  Aedes aegypti Aag-2 Cell Proteome Modulation in Response to Chikungunya Virus Infection.

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Journal:  Front Cell Infect Microbiol       Date:  2022-06-15       Impact factor: 6.073

6.  Photocleavable Surfactant-Enabled Extracellular Matrix Proteomics.

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Journal:  Anal Chem       Date:  2020-11-24       Impact factor: 6.986

7.  NANOG/NANOGP8 Localizes at the Centrosome and is Spatiotemporally Associated with Centriole Maturation.

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8.  Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis.

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Journal:  Nat Commun       Date:  2020-04-09       Impact factor: 14.919

9.  Binary Classifier for Computing Posterior Error Probabilities in MetaMorpheus.

Authors:  Michael R Shortreed; Robert J Millikin; Lei Liu; Zach Rolfs; Rachel M Miller; Leah V Schaffer; Brian L Frey; Lloyd M Smith
Journal:  J Proteome Res       Date:  2021-03-08       Impact factor: 4.466

10.  Multi-omics Visualization Platform: An extensible Galaxy plug-in for multi-omics data visualization and exploration.

Authors:  Thomas McGowan; James E Johnson; Praveen Kumar; Ray Sajulga; Subina Mehta; Pratik D Jagtap; Timothy J Griffin
Journal:  Gigascience       Date:  2020-04-01       Impact factor: 7.658

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