Towards Quality Control for DNA Microarrays

Smith, Kaleigh; Hallett, Michael

doi:10.1089/cmb.2004.11.945

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Gautier et al (2004b) investigate the effect of updating the mapping of probes to genes on the estimated expression values. Smith and Hallett (2004) define four types of degenerate probe behaviour based on free energy computations and pattern recognition. Finkelstein (2005) evaluated the Affymetrix quality reports of over 5,000 chips collected by St. Jude Children's Research Hospital over a period of three years, and linked some quality trends to experimental conditions.…”

Section: • Effects Of Particular Hybridization Conditions and Sample ...mentioning

confidence: 99%

Quality Assessment for Short Oligonucleotide Microarray Data

Brettschneider¹,

Collin²,

Bolstad³

et al. 2008

Technometrics

119

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Quality of microarray gene expression data has emerged as a new research topic. As in other areas, microarray quality is assessed by comparing suitable numerical summaries across microarrays, so that outliers and trends can be visualized and poor-quality arrays or variable-quality sets of arrays can be identified. Because each single array comprises tens or hundreds of thousands of measurements, the challenge is to find numerical summaries that can be used to make accurate quality calls. Toward this end, several new quality measures are introduced based on probe-level and probeset-level information, all obtained as a byproduct of the low-level analysis algorithms RMA/fitPLM for Affymetrix GeneChips. Quality landscapes spatially localize chip or hybridization problems. Numerical chip quality measures are derived from the distributions of normalized unscaled standard errors and relative log expressions. Quality of chip batches is assessed by residual scale factors. These quality assessment measures are demonstrated on a variety of data sets, including spike-in experiments, small lab experiments, and multisite studies. They are compared with Affymetrix's individual chip quality report.

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Section: • Effects Of Particular Hybridization Conditions and Sample ...mentioning

confidence: 99%

Quality Assessment for Short Oligonucleotide Microarray Data

Brettschneider¹,

Collin²,

Bolstad³

et al. 2008

Technometrics

119

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“…Agilent and Codelink both use single probes to target a gene, but the Affymetrix U95Av2 genechip utilizes probe sets consisting of 16 probes to target a gene. Probe set gene expression measurements are statistical summarizations of member probes, which can be influenced by dead probes, cross-hybridization and other effects [ 16 , 17 ]. In order to generate a clearer view of expression measurements and agreement levels, we thought to analyze probe-level expression vectors instead of probe set summarizations for Affymetrix platform combinations.…”

Section: Resultsmentioning

confidence: 99%

A detailed transcript-level probe annotation reveals alternative splicing based microarray platform differences

et al. 2007

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Background: Microarrays are a popular tool used in experiments to measure gene expression levels. Improving the reproducibility of microarray results produced by different chips from various manufacturers is important to create comparable and combinable experimental results. Alternative splicing has been cited as a possible cause of differences in expression measurements across platforms, though no study to this point has been conducted to show its influence in cross-platform differences.

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“…Our software is sufficiently robust as to carry out these experiments with a ten fold increase in the number of hybridization experiments. We have made several clarifications and improvements to the framework in [22].…”

Section: Resultsmentioning

confidence: 99%