Comprehensive quality control utilizing the prehybridization third-dye image leads to accurate gene expression measurements by cDNA microarrays

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• 作者：Xujing Wang (1) (2)
  Shuang Jia (1) (2)
  Lisa Meyer (1) (2)
  Bixia Xiang (1) (2)
  Li-Yen Chen (2)
  Nan Jiang (3)
  Carol Moreno (2)
  Howard J Jacob (2)
  Soumitra Ghosh (1) (2)
  Martin J Hessner (1) (2)
  
• 刊名：BMC Bioinformatics
• 出版年：2006
• 出版时间：December 2006
• 年：2006
• 卷：7
• 期：1
• 全文大小：1442KB
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• 作者单位：Xujing Wang (1) (2)
  Shuang Jia (1) (2)
  Lisa Meyer (1) (2)
  Bixia Xiang (1) (2)
  Li-Yen Chen (2)
  Nan Jiang (3)
  Carol Moreno (2)
  Howard J Jacob (2)
  Soumitra Ghosh (1) (2)
  Martin J Hessner (1) (2)
  
  1. The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Children's Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
  2. The Human and Molecular Genetics Center, The Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
  3. NimbleGen Systems Inc, 1 Science Court, Madison, WI, 53711, USA
  
• ISSN：1471-2105

文摘

Background Gene expression profiling using microarrays has become an important genetic tool. Spotted arrays prepared in academic labs have the advantage of low cost and high design and content flexibility, but are often limited by their susceptibility to quality control (QC) issues. Previously, we have reported a novel 3-color microarray technology that enabled array fabrication QC. In this report we further investigated its advantage in spot-level data QC. Results We found that inadequate amount of bound probes available for hybridization led to significant, gene-specific compression in ratio measurements, increased data variability, and printing pin dependent heterogeneities. The impact of such problems can be captured through the definition of quality scores, and efficiently controlled through quality-dependent filtering and normalization. We compared gene expression measurements derived using our data processing pipeline with the known input ratios of spiked in control clones, and with the measurements by quantitative real time RT-PCR. In each case, highly linear relationships (R2>0.94) were observed, with modest compression in the microarray measurements (correction factor<1.17). Conclusion Our microarray analytical and technical advancements enabled a better dissection of the sources of data variability and hence a more efficient QC. With that highly accurate gene expression measurements can be achieved using the cDNA microarray technology.