ArticleGene regulation and systems biology2008
Image analysis and data normalization procedures are crucial for microarray analyses.
Article in Gene regulation and systems biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Comparative Gene Expression Analysis of Two Mouse Models of Autism: Transcriptome Profiling of the BTBR and En2 (-/-) Hippocampus.Frontiers in neuroscience · 2016Article
- Gene expression rate comparison for multiple high-throughput datasets.IET systems biology · 2013Article
- Application of Top-Down and Bottom-up Systems Approaches in Ruminant Physiology and Metabolism.Current genomics · 2012Article
- A glance at DNA microarray technology and applications.BioImpacts : BI · 2011Article
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Authors and funding
7 authors.
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Abstract
This study was conducted with the aim of optimizing the experimental design of array experiments. We compared two image analysis and normalization procedures prior to data analysis using two experimental designs. For this, RNA samples from Charolais steers Longissimus thoracis muscle and subcutaneous adipose tissues were labeled and hybridized to a bovine 8,400 oligochip either in triplicate or in a dye-swap design. Image analysis and normalization were processed by either GenePix/MadScan or ImaGene/GeneSight. Statistical data analysis was then run using either the SAM method or a Student's t-test using a multiple test correction run on R 2.1 software. Our results show that image analysis and normalization procedure had an impact whereas the statistical methods much less influenced the outcome of differentially expressed genes. Image analysis and data normalization are thus an important aspect of microarray experiments, having a potentially significant impact on downstream analyses such as the identification of differentially expressed genes. This study provides indications on the choice of raw data preprocessing in microarray technology.
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