Literature DB >> 20121475

Role of spectral counting in quantitative proteomics.

Deborah H Lundgren1, Sun-Il Hwang, Linfeng Wu, David K Han.   

Abstract

Spectral count, defined as the total number of spectra identified for a protein, has gained acceptance as a practical, label-free, semiquantitative measure of protein abundance in proteomic studies. In this review, we discuss issues affecting the performance of spectral counting relative to other label-free methods, as well as its limitations. Possible consequences of modifications, which are commonly applied to raw spectral counts to improve abundance estimations, are considered. The use of spectral counting for different types of quantitation studies is explored and critiqued. Different statistical methods and underlying frameworks that have been applied to spectral count analysis are described and compared, and problem areas that undermine confident statistical analysis are considered. Finally, the issue of accurate estimation of false-discovery rates is addressed and identified as a major current challenge in quantitative proteomics.

Mesh:

Year:  2010        PMID: 20121475     DOI: 10.1586/epr.09.69

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  146 in total

1.  Distinct energy metabolism of auditory and vestibular sensory epithelia revealed by quantitative mass spectrometry using MS2 intensity.

Authors:  Kateri J Spinelli; John E Klimek; Phillip A Wilmarth; Jung-Bum Shin; Dongseok Choi; Larry L David; Peter G Gillespie
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-17       Impact factor: 11.205

2.  msCompare: a framework for quantitative analysis of label-free LC-MS data for comparative candidate biomarker studies.

Authors:  Berend Hoekman; Rainer Breitling; Frank Suits; Rainer Bischoff; Peter Horvatovich
Journal:  Mol Cell Proteomics       Date:  2012-02-07       Impact factor: 5.911

Review 3.  Using proteomics to study sexual reproduction in angiosperms.

Authors:  Ján A Miernyk; Anna Preťová; Adela Olmedilla; Katarína Klubicová; Bohuš Obert; Martin Hajduch
Journal:  Sex Plant Reprod       Date:  2010-09-10

4.  Evaluation of normalization methods on GeLC-MS/MS label-free spectral counting data to correct for variation during proteomic workflows.

Authors:  Emine Gokce; Christopher M Shuford; William L Franck; Ralph A Dean; David C Muddiman
Journal:  J Am Soc Mass Spectrom       Date:  2011-09-24       Impact factor: 3.109

5.  Proteomic profiling of a robust Wolbachia infection in an Aedes albopictus mosquito cell line.

Authors:  Gerald D Baldridge; Abigail S Baldridge; Bruce A Witthuhn; LeeAnn Higgins; Todd W Markowski; Ann M Fallon
Journal:  Mol Microbiol       Date:  2014-09-22       Impact factor: 3.501

6.  Proteome analysis of the triton-insoluble erythrocyte membrane skeleton.

Authors:  Avik Basu; Sandra Harper; Esther N Pesciotta; Kaye D Speicher; Abhijit Chakrabarti; David W Speicher
Journal:  J Proteomics       Date:  2015-08-10       Impact factor: 4.044

Review 7.  Proteomics characterization of exosome cargo.

Authors:  Kevin L Schey; J Matthew Luther; Kristie L Rose
Journal:  Methods       Date:  2015-03-31       Impact factor: 3.608

8.  Proteomic profile of the lens in a streptozotocin-induced diabetic rat model using shotgun proteomics.

Authors:  Noriaki Nagai; Tetsushi Yamamoto; Kuniko Mitamura; Atsushi Taga
Journal:  Biomed Rep       Date:  2017-09-22

9.  Total and putative surface proteomics of malaria parasite salivary gland sporozoites.

Authors:  Scott E Lindner; Kristian E Swearingen; Anke Harupa; Ashley M Vaughan; Photini Sinnis; Robert L Moritz; Stefan H I Kappe
Journal:  Mol Cell Proteomics       Date:  2013-01-16       Impact factor: 5.911

10.  Proteomic classification of acute leukemias by alignment-based quantitation of LC-MS/MS data sets.

Authors:  Eric J Foss; Dragan Radulovic; Derek L Stirewalt; Jerald Radich; Olga Sala-Torra; Era L Pogosova-Agadjanyan; Shawna M Hengel; Keith R Loeb; H Joachim Deeg; Soheil Meshinchi; David R Goodlett; Antonio Bedalov
Journal:  J Proteome Res       Date:  2012-09-11       Impact factor: 4.466

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