Literature DB >> 17049036

Approximate sample size calculations with microarray data: an illustration.

José A Ferreira1, Aeilko Zwinderman.   

Abstract

We outline a method of sample size calculation in microarray experiments on the basis of pilot data and illustrate its practical application with both simulated and real data. The method was shown to be consistent (as the number of 'probed genes' tends to infinity) under general conditions in an earlier, more 'theoretical' companion paper. Its implementation requires the values of test statistics, the sample size with which the statistics are computed, and the knowledge of their distribution under the null hypothesis.

Mesh:

Year:  2006        PMID: 17049036     DOI: 10.2202/1544-6115.1227

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


  14 in total

1.  Practical guidelines for assessing power and false discovery rate for a fixed sample size in microarray experiments.

Authors:  Tiejun Tong; Hongyu Zhao
Journal:  Stat Med       Date:  2008-05-20       Impact factor: 2.373

2.  Exact calculations of average power for the Benjamini-Hochberg procedure.

Authors:  Deborah H Glueck; Jan Mandel; Anis Karimpour-Fard; Lawrence Hunter; Keith E Muller
Journal:  Int J Biostat       Date:  2008       Impact factor: 0.968

3.  Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset.

Authors:  Qianqian Zhu; Jeffrey C Miecznikowski; Marc S Halfon
Journal:  BMC Bioinformatics       Date:  2010-05-27       Impact factor: 3.169

4.  CGHpower: exploring sample size calculations for chromosomal copy number experiments.

Authors:  Ilari Scheinin; José A Ferreira; Sakari Knuutila; Gerrit A Meijer; Mark A van de Wiel; Bauke Ylstra
Journal:  BMC Bioinformatics       Date:  2010-06-17       Impact factor: 3.169

5.  Statistical analysis in metabolic phenotyping.

Authors:  Benjamin J Blaise; Gonçalo D S Correia; Gordon A Haggart; Izabella Surowiec; Caroline Sands; Matthew R Lewis; Jake T M Pearce; Johan Trygg; Jeremy K Nicholson; Elaine Holmes; Timothy M D Ebbels
Journal:  Nat Protoc       Date:  2021-07-28       Impact factor: 13.491

6.  A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data.

Authors:  Maria Vinaixa; Sara Samino; Isabel Saez; Jordi Duran; Joan J Guinovart; Oscar Yanes
Journal:  Metabolites       Date:  2012-10-18

7.  Relative power and sample size analysis on gene expression profiling data.

Authors:  M van Iterson; P A C 't Hoen; P Pedotti; G J E J Hooiveld; J T den Dunnen; G J B van Ommen; J M Boer; R X Menezes
Journal:  BMC Genomics       Date:  2009-09-17       Impact factor: 3.969

8.  Gene expression profiles of sporadic canine hemangiosarcoma are uniquely associated with breed.

Authors:  Beth A Tamburini; Susan Trapp; Tzu Lip Phang; Jill T Schappa; Lawrence E Hunter; Jaime F Modiano
Journal:  PLoS One       Date:  2009-05-20       Impact factor: 3.240

9.  dsRNA-induced changes in gene expression profiles of primary nasal and bronchial epithelial cells from patients with asthma, rhinitis and controls.

Authors:  Ariane H Wagener; Aeilko H Zwinderman; Silvia Luiten; Wytske J Fokkens; Elisabeth H Bel; Peter J Sterk; Cornelis M van Drunen
Journal:  Respir Res       Date:  2014-01-29

10.  The impact of allergic rhinitis and asthma on human nasal and bronchial epithelial gene expression.

Authors:  Ariane H Wagener; Aeilko H Zwinderman; Silvia Luiten; Wytske J Fokkens; Elisabeth H Bel; Peter J Sterk; Cornelis M van Drunen
Journal:  PLoS One       Date:  2013-11-25       Impact factor: 3.240

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