Literature DB >> 19053145

Sample size determination in clinical proteomic profiling experiments using mass spectrometry for class comparison.

David A Cairns1, Jennifer H Barrett, Lucinda J Billingham, Anthea J Stanley, George Xinarianos, John K Field, Phillip J Johnson, Peter J Selby, Rosamonde E Banks.   

Abstract

Mass spectrometric profiling approaches such as MALDI-TOF and SELDI-TOF are increasingly being used in disease marker discovery, particularly in the lower molecular weight proteome. However, little consideration has been given to the issue of sample size in experimental design. The aim of this study was to develop a protocol for the use of sample size calculations in proteomic profiling studies using MS. These sample size calculations can be based on a simple linear mixed model which allows the inclusion of estimates of biological and technical variation inherent in the experiment. The use of a pilot experiment to estimate these components of variance is investigated and is shown to work well when compared with larger studies. Examination of data from a number of studies using different sample types and different chromatographic surfaces shows the need for sample- and preparation-specific sample size calculations.

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Year:  2009        PMID: 19053145     DOI: 10.1002/pmic.200800417

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  16 in total

1.  Proteomic profiling of cerebrospinal fluid identifies prostaglandin D2 synthase as a putative biomarker for pediatric medulloblastoma: A pediatric brain tumor consortium study.

Authors:  Meena U Rajagopal; Yetrib Hathout; Tobey J MacDonald; Mark W Kieran; Sri Gururangan; Susan M Blaney; Peter Phillips; Roger Packer; Heather Gordish-Dressman; Brian R Rood
Journal:  Proteomics       Date:  2011-01-27       Impact factor: 3.984

2.  Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data.

Authors:  Karin Schork; Katharina Podwojski; Michael Turewicz; Christian Stephan; Martin Eisenacher
Journal:  Methods Mol Biol       Date:  2021

Review 3.  Proteomic urinary biomarker approach in renal disease: from discovery to implementation.

Authors:  Joost P Schanstra; Harald Mischak
Journal:  Pediatr Nephrol       Date:  2014-03-15       Impact factor: 3.714

4.  Characterising salivary peptidome across diurnal dynamics and variations induced by sampling procedures.

Authors:  Ce Zhu; Chao Yuan; Fangqiao Wei; Xiangyu Sun; Shuguo Zheng
Journal:  Clin Oral Investig       Date:  2022-09-23       Impact factor: 3.606

Review 5.  Biomarker discovery in mass spectrometry-based urinary proteomics.

Authors:  Samuel Thomas; Ling Hao; William A Ricke; Lingjun Li
Journal:  Proteomics Clin Appl       Date:  2016-02-11       Impact factor: 3.494

6.  Circulating cytokine portraits can differentiate between allograft rejection and pulmonary infection in cardiac transplant rats.

Authors:  Hao Chen; Feng Li; Yanxia Zhan; Weiyong Yu; Chen Lu; Yunfeng Cheng; Yunqing Mei
Journal:  Interact Cardiovasc Thorac Surg       Date:  2016-03-22

7.  Addressing the challenge of defining valid proteomic biomarkers and classifiers.

Authors:  Mohammed Dakna; Keith Harris; Alexandros Kalousis; Sebastien Carpentier; Walter Kolch; Joost P Schanstra; Marion Haubitz; Antonia Vlahou; Harald Mischak; Mark Girolami
Journal:  BMC Bioinformatics       Date:  2010-12-10       Impact factor: 3.169

8.  Protein differences between human trapezius and vastus lateralis muscles determined with a proteomic approach.

Authors:  Jenny Hadrévi; Fredrik Hellström; Thomas Kieselbach; Christer Malm; Fatima Pedrosa-Domellöf
Journal:  BMC Musculoskelet Disord       Date:  2011-08-10       Impact factor: 2.362

9.  An individual urinary proteome analysis in normal human beings to define the minimal sample number to represent the normal urinary proteome.

Authors:  Xuejiao Liu; Chen Shao; Lilong Wei; Jindan Duan; Shuzhen Wu; Xuewang Li; Mingxi Li; Wei Sun
Journal:  Proteome Sci       Date:  2012-11-21       Impact factor: 2.480

10.  Integrated multi-level quality control for proteomic profiling studies using mass spectrometry.

Authors:  David A Cairns; David N Perkins; Anthea J Stanley; Douglas Thompson; Jennifer H Barrett; Peter J Selby; Rosamonde E Banks
Journal:  BMC Bioinformatics       Date:  2008-12-04       Impact factor: 3.169

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