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Microarray Quality Evaluation and Process Step Identification System

The goal of this system is to evaluate the quality of microarray data for identifying process steps with failures. It includes array design, spike controls, negative controls, and statistical analysis tools like Transcount and MA/IR plot statistics for quality assessment. Normalization methods based on expression data and spike controls are employed, and quality indicators and reports are generated. Results are stored in BASE for procedure refinement and trend identification.

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Microarray Quality Evaluation and Process Step Identification System

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  1. QC system Norwegian Microarray Consortium(Inge J) • Goal: • Evaluate quality, allow identification of process step with failure • Array design • Spike controls – >50 arabidopsis probes – for human, mouse, rat oligo chips (Operon) • Negative controls • Spike mix • Span intensity and ratio spectrum • Basis for quality assessment • Transcount (Hovig et al) – statistical analysis aiming to quantify transcript counts • Single spot statistics • MA/IR plot statistic (banana factor etc) • Normalisation based on expression data – statistics based on the spikes? • Normalisation based on spikes – statistics based on expression data? • Quality indicators/reports • Numbers, plots • Incorporate in standard NMC service, internal qc and assurance towards users • Store results in BASE – allow refinement of procedure and identification of trends

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