Literature DB >> 33500498

Multi-Q 2 software facilitates isobaric labeling quantitation analysis with improved accuracy and coverage.

Ching-Tai Chen1, Jen-Hung Wang2,3,4, Cheng-Wei Cheng5, Wei-Che Hsu2, Chu-Ling Ko6, Wai-Kok Choong2, Ting-Yi Sung7.   

Abstract

Mass spectrometry-based proteomics using isobaric labeling for multiplex quantitation has become a popular approach for proteomic studies. We present Multi-Q 2, an isobaric-labeling quantitation tool which can yield the largest quantitation coverage and improved quantitation accuracy compared to three state-of-the-art methods. Multi-Q 2 supports identification results from several popular proteomic data analysis platforms for quantitation, offering up to 12% improvement in quantitation coverage for accepting identification results from multiple search engines when compared with MaxQuant and PatternLab. It is equipped with various quantitation algorithms, including a ratio compression correction algorithm, and results in up to 336 algorithmic combinations. Systematic evaluation shows different algorithmic combinations have different strengths and are suitable for different situations. We also demonstrate that the flexibility of Multi-Q 2 in customizing algorithmic combination can lead to improved quantitation accuracy over existing tools. Moreover, the use of complementary algorithmic combinations can be an effective strategy to enhance sensitivity when searching for biomarkers from differentially expressed proteins in proteomic experiments. Multi-Q 2 provides interactive graphical interfaces to process quantitation and to display ratios at protein, peptide, and spectrum levels. It also supports a heatmap module, enabling users to cluster proteins based on their abundance ratios and to visualize the clustering results. Multi-Q 2 executable files, sample data sets, and user manual are freely available at http://ms.iis.sinica.edu.tw/COmics/Software_Multi-Q2.html .

Entities:  

Year:  2021        PMID: 33500498      PMCID: PMC7838301          DOI: 10.1038/s41598-021-81740-4

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  50 in total

1.  Open mass spectrometry search algorithm.

Authors:  Lewis Y Geer; Sanford P Markey; Jeffrey A Kowalak; Lukas Wagner; Ming Xu; Dawn M Maynard; Xiaoyu Yang; Wenyao Shi; Stephen H Bryant
Journal:  J Proteome Res       Date:  2004 Sep-Oct       Impact factor: 4.466

2.  MSnbase-an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation.

Authors:  Laurent Gatto; Kathryn S Lilley
Journal:  Bioinformatics       Date:  2011-11-22       Impact factor: 6.937

3.  MilQuant: a free, generic software tool for isobaric tagging-based quantitation.

Authors:  Xiao Zou; Minzhi Zhao; Hongyan Shen; Xuyang Zhao; Yuanpeng Tong; Qingsong Wang; Shicheng Wei; Jianguo Ji
Journal:  J Proteomics       Date:  2012-07-10       Impact factor: 4.044

4.  iPQF: a new peptide-to-protein summarization method using peptide spectra characteristics to improve protein quantification.

Authors:  Martina Fischer; Bernhard Y Renard
Journal:  Bioinformatics       Date:  2015-11-20       Impact factor: 6.937

5.  iTRAQ underestimation in simple and complex mixtures: "the good, the bad and the ugly".

Authors:  Saw Yen Ow; Malinda Salim; Josselin Noirel; Caroline Evans; Ishtiaq Rehman; Phillip C Wright
Journal:  J Proteome Res       Date:  2009-11       Impact factor: 4.466

6.  Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium.

Authors:  Matthew J Ellis; Michael Gillette; Steven A Carr; Amanda G Paulovich; Richard D Smith; Karin K Rodland; R Reid Townsend; Christopher Kinsinger; Mehdi Mesri; Henry Rodriguez; Daniel C Liebler
Journal:  Cancer Discov       Date:  2013-10       Impact factor: 39.397

7.  Andromeda: a peptide search engine integrated into the MaxQuant environment.

Authors:  Jürgen Cox; Nadin Neuhauser; Annette Michalski; Richard A Scheltema; Jesper V Olsen; Matthias Mann
Journal:  J Proteome Res       Date:  2011-02-22       Impact factor: 4.466

8.  IQuant: an automated pipeline for quantitative proteomics based upon isobaric tags.

Authors:  Bo Wen; Ruo Zhou; Qiang Feng; Quanhui Wang; Jun Wang; Siqi Liu
Journal:  Proteomics       Date:  2014-09-05       Impact factor: 3.984

9.  Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0.

Authors:  Paulo C Carvalho; Diogo B Lima; Felipe V Leprevost; Marlon D M Santos; Juliana S G Fischer; Priscila F Aquino; James J Moresco; John R Yates; Valmir C Barbosa
Journal:  Nat Protoc       Date:  2015-12-10       Impact factor: 13.491

Review 10.  Isobaric labeling-based relative quantification in shotgun proteomics.

Authors:  Navin Rauniyar; John R Yates
Journal:  J Proteome Res       Date:  2014-11-04       Impact factor: 4.466

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