Literature DB >> 22789671

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

Xiao Zou1, Minzhi Zhao, Hongyan Shen, Xuyang Zhao, Yuanpeng Tong, Qingsong Wang, Shicheng Wei, Jianguo Ji.   

Abstract

Isobaric tagging techniques such as iTRAQ and TMT are widely used in quantitative proteomics and especially useful for samples that demand in vitro labeling. Due to diversity in choices of MS acquisition approaches, identification algorithms, and relative abundance deduction strategies, researchers are faced with a plethora of possibilities when it comes to data analysis. However, the lack of generic and flexible software tool often makes it cumbersome for researchers to perform the analysis entirely as desired. In this paper, we present MilQuant, mzXML-based isobaric labeling quantitator, a pipeline of freely available programs that supports native acquisition files produced by all mass spectrometer types and collection approaches currently used in isobaric tagging based MS data collection. Moreover, aside from effective normalization and abundance ratio deduction algorithms, MilQuant exports various intermediate results along each step of the pipeline, making it easy for researchers to customize the analysis. The functionality of MilQuant was demonstrated by four distinct datasets from different laboratories. The compatibility and extendibility of MilQuant makes it a generic and flexible tool that can serve as a full solution to data analysis of isobaric tagging-based quantitation.
Copyright © 2012 Elsevier B.V. All rights reserved.

Mesh:

Year:  2012        PMID: 22789671     DOI: 10.1016/j.jprot.2012.06.028

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  3 in total

1.  IsoProt: A Complete and Reproducible Workflow To Analyze iTRAQ/TMT Experiments.

Authors:  Johannes Griss; Goran Vinterhalter; Veit Schwämmle
Journal:  J Proteome Res       Date:  2019-03-20       Impact factor: 4.466

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

Authors:  Ching-Tai Chen; Jen-Hung Wang; Cheng-Wei Cheng; Wei-Che Hsu; Chu-Ling Ko; Wai-Kok Choong; Ting-Yi Sung
Journal:  Sci Rep       Date:  2021-01-26       Impact factor: 4.379

Review 3.  Quantitative Proteomics Using Isobaric Labeling: A Practical Guide.

Authors:  Xiulan Chen; Yaping Sun; Tingting Zhang; Lian Shu; Peter Roepstorff; Fuquan Yang
Journal:  Genomics Proteomics Bioinformatics       Date:  2022-01-08       Impact factor: 6.409

  3 in total

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