An assessment of Motorola CodeLink microarray performance for gene expression profiling applications.
Ramesh Ramakrishnan,David Dorris,Anna Lublinsky,Allen Nguyen,Marc Domanus,Anna Prokhorova,Linn Gieser,Edward Touma,Randall Lockner,Murthy Tata,Xiaomei Zhu,Marcus Patterson,Richard Shippy,Timothy J. Sendera,Abhijit Mazumder +14 more
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TLDR
This work demonstrates three significant advantages of the Motorola CodeLink platform: sensitivity of one copy per cell, coefficients of variation in the hybridization signals across slides and across target preparations, and specificity in distinguishing highly homologous sequences.Abstract:
DNA microarrays enable users to obtain information on differences in transcript abundance on a massively parallel scale. Recently, however, data analyses have revealed potential pitfalls related to image acquisition, variability and misclassifications in replicate measurements, cross-hybridization and sensitivity limitations. We have generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. Together, we have used these tools to optimize performance in an expression profiling study. We demonstrate three significant advantages of the Motorola CodeLink™ platform: sensitivity of one copy per cell, coefficients of variation of 10% in the hybridization signals across slides and across target preparations, and specificity in distinguishing highly homologous sequences. Slides where oligonucleotide probes are spotted in 6-fold redundancy were used to demonstrate the effect of replication on data quality. Lastly, the differential expression ratios obtained with the CodeLink™ expression platform were validated against those obtained with quantitative reverse transcription–PCR assays for 54 genes.read more
Citations
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miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting.
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Human hepatic stellate cell lines, LX-1 and LX-2: new tools for analysis of hepatic fibrosis
L Xu,A Y Hui,Efsevia Albanis,Michael J. P. Arthur,Sheila M. O'Byrne,William S. Blaner,P Mukherjee,Scott L. Friedman,F J Eng +8 more
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Microarray-based, high-throughput gene expression profiling of microRNAs
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