Literature DB >> 15038166

Amplification protocols introduce systematic but reproducible errors into gene expression studies.

Claire L Wilson1, Stuart D Pepper, Yvonne Hey, Crispin J Miller.   

Abstract

The desire to perform microarray experiments with small starting amounts of RNA has led to the development of a variety of protocols for preparing and amplifying mRNA. This has consequences not only for the standardization of experimental design, but also for reproducibility and comparability between experiments. Here we investigate the differences between the Affymetrix standard and small sample protocols and address the data analysis issues that arise when comparing samples and experiments that have been processed in different ways. We show that data generated on the same platform using different protocols are not directly comparable. Further, protocols introduce systematic biases that can be largely accounted for by using the correct data analysis techniques.

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Year:  2004        PMID: 15038166     DOI: 10.2144/04363RN05

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  26 in total

Review 1.  Technical variables in high-throughput miRNA expression profiling: much work remains to be done.

Authors:  Peter T Nelson; Wang-Xia Wang; Bernard R Wilfred; Guiliang Tang
Journal:  Biochim Biophys Acta       Date:  2008-04-07

2.  Single-cell expression profiling of human epidermal stem and transit-amplifying cells: Lrig1 is a regulator of stem cell quiescence.

Authors:  Kim B Jensen; Fiona M Watt
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-28       Impact factor: 11.205

3.  Cardiac pressure overload hypertrophy is differentially regulated by β-adrenergic receptor subtypes.

Authors:  Mingming Zhao; Giovanni Fajardo; Takashi Urashima; Joshua M Spin; Sara Poorfarahani; Viswanathan Rajagopalan; Diem Huynh; Andrew Connolly; Thomas Quertermous; Daniel Bernstein
Journal:  Am J Physiol Heart Circ Physiol       Date:  2011-06-24       Impact factor: 4.733

4.  Detection of differentially expressed glycogenes in trabecular meshwork of eyes with primary open-angle glaucoma.

Authors:  Shiri Diskin; Janardan Kumar; Zhiyi Cao; Joel S Schuman; Tim Gilmartin; Steven R Head; Noorjahan Panjwani
Journal:  Invest Ophthalmol Vis Sci       Date:  2006-04       Impact factor: 4.799

5.  Differential expression of genes within the cochlea as defined by a custom mouse inner ear microarray.

Authors:  Ken A Morris; Einat Snir; Celine Pompeia; Irina V Koroleva; Bechara Kachar; Yoshihide Hayashizaki; Piero Carninci; M Bento Soares; Kirk W Beisel
Journal:  J Assoc Res Otolaryngol       Date:  2005-04-22

6.  Long Non-coding RNA Expression Profiling Using Arraystar LncRNA Microarrays.

Authors:  Yanggu Shi; Jindong Shang
Journal:  Methods Mol Biol       Date:  2021

7.  Selective amplification of Brucella melitensis mRNA from a mixed host-pathogen total RNA.

Authors:  Carlos A Rossetti; Cristi L Galindo; Harold R Garner; L Garry Adams
Journal:  BMC Res Notes       Date:  2010-09-28

8.  Accurate expression profiling of very small cell populations.

Authors:  Eva Gonzalez-Roca; Xabier Garcia-Albéniz; Silvia Rodriguez-Mulero; Roger R Gomis; Karl Kornacker; Herbert Auer
Journal:  PLoS One       Date:  2010-12-28       Impact factor: 3.240

9.  Statistical evaluation of transcriptomic data generated using the Affymetrix one-cycle, two-cycle and IVT-Express RNA labelling protocols with the Arabidopsis ATH1 microarray.

Authors:  Tara J Holman; Michael H Wilson; Kim Kenobi; Ian L Dryden; T Charlie Hodgman; Andrew Ta Wood; Michael J Holdsworth
Journal:  Plant Methods       Date:  2010-03-15       Impact factor: 4.993

10.  "Hook"-calibration of GeneChip-microarrays: chip characteristics and expression measures.

Authors:  Hans Binder; Knut Krohn; Stephan Preibisch
Journal:  Algorithms Mol Biol       Date:  2008-08-29       Impact factor: 1.405

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