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Dilution/Mixture Study Bill Craven, GeneLogic, Inc.

This study investigates the variability in post-hybridization analysis and the impact of different dilution and mixture ratios on gene expression estimates using HGU95A assays. Two sample types, human liver and a central nervous system cell line, were chosen to ensure independent expression profiles. Each dilution was assessed with five replicates across five scanners, while incorporating bacterial spike-ins for control. Key findings revealed that lower total cRNA concentrations led to higher spike-in signals, highlighting non-linearities and saturation effects which need further investigation.

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Dilution/Mixture Study Bill Craven, GeneLogic, Inc.

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  1. Dilution/Mixture StudyBill Craven, GeneLogic, Inc. • Motivated by a desire for a data set to be used as a baseline to characterize analysis and normalization methods • We wanted to examine: • Post-hybridization variability (i.e. scanner effects) • Effects on differential expression estimates compared to known dilution and/or mixing ratios

  2. Design • Dilutions and mixtures taken out of master IVT preparations pooled for two samples: human liver (sample A) and a central nervous system cell line (sample B). These were chosen to maximize independence of expression. • Each dilution or mixture had five replicate HGU95A assays run on five scanners. • The concentration of each material is characterized by the number of ug of labeled cRNA in the individual hybridization solutions. • All examples had Genelogic’s standard bacterial spikeins added at their nominal concentrations to give an absolute control.

  3. Design summary:

  4. Unnormalized, MAS 5.0

  5. Standard Curve Normalized, MAS 5.0

  6. Adjusted Trimmed Mean Normalization, MAS 5.0

  7. Initial Observations • A fundamental assumption behind our dilution study was that the assays are independent of total cRNA in the hybridization mixture. • A quick examination of the raw intensities of the spikeins tells us this isn’t the case; there appears to be a chemical saturation effect whereby at lower total cRNA concentrations, the spike-in signals are higher (this is confirmed at the probe level). • Furthermore, this effect introduces significant non-linearities to the expression in the bulk of the sample observed.

  8. Median spike-in Intensities vs total RNA MAS 5 Intensity Total RNA, mg 11 Randomly selected probe set medians vs total RNA MAS 5 Intensity Total RNA, mg

  9. Log2 Intensities, M vs A: Liver 1.25 ug – Liver 20 ug, scanner 1 Spike-in Nominal Ratio Spike-ins Nominal Ratio = log2(1.25/20)

  10. Looking Forward • Further Work: • Complete analysis of dilutions to characterize and normalize out the observed non-linearities • Check observed fold changes against nominal ratios for various methods of analysis • Finally, check for unexpected effects in the mixture cases, indicating some background competition • Acknowledgments: • Terry Speed, Harry Zuzan, Francois Collin for improvements in the design • Uwe Scherf, Yasmin Beazer-Barclay for making the wet-lab part happen!

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