1. Quality control of Affymetrix arrays

2. What can go wrong? RNA degradation (before hyb) –3’/5’ Dirty samples –background, % present calls Uneven hybridizations (during hyb) –RLE, NUSE Machine problems

3. If >10%, Affymetrix may provide with new array

4. Report Type:Expression Report Date: 11:00AM 07/01/2003 ______________________________________________________________________ Filename:030701RE_U133A_PS1.CHP Probe Array Type:HG-U133A Algorithm:Statistical Probe Pair Thr:8 Controls:Antisense ______________________________________________________________________ Alpha1:0.05 Alpha2:0.065 Tau:0.015 Noise (RawQ):1.970 Scale Factor (SF):0.943 TGT Value:200 Norm Factor (NF):1.000 ______________________________________________________________________ Background: Avg: 44.89Std: 0.81Min: 43.10Max: 47.30 Noise: Avg: 2.27Std: 0.14Min: 2.00Max: 2.80 ___________________________________________________________________ Total Probe Sets:22283 Number Present:1193353.6% Number Absent:1004045.1% Number Marginal:3101.4% Average Signal (P):525.7 Average Signal (A):17.8 Average Signal (M):55.8 Average Signal (All):290.3 ______________________________________________________________________ Housekeeping Controls: Probe SetSig(5')Det(5')Sig(M')Det(M')Sig(3')Det(3') Sig(all) Sig(3'/5') HUMISGF3A/M97935537.6P828.6P1760.2P1042.123.27 HUMRGE/M100988.3A3.9A40.8A17.674.94 HUMGAPDH/M331978498.0P7917.8P7937.1P8117.620.93 HSAC07/X003518335.5P8679.7P9096.8P8704.001.09 M27830104.1P135.1A11.6A83.590.11 ______________________________________________________________________ MAS5 report

5. RNA degradation 3’/5’ ratios of GAPDH AffyRNAdeg in package ‘affy’ –3’/5’ ratios for all genes on the array

6. RNA degradation

7. Results show that RNA degradation is reproducible when making technical duplicates

8. affyPLM Library to work with probes fitPLM() –fits a linear model with probe effect

9. affyPLM

10. image(cel.f) –plots weights from fit

11. Relative Log Expression RLE(affybatch) –the expression value of one array compared to median of all

12. Normalized Unscaled Standard Errors NUSE(affybatch)

13. RLE NUSE

15. Solution Uneven hybridizations: normalization takes care of RNA degradation: outliers problematic High background: the results will not be as clear, but trends can still be seen –Bioinformatics and Computational Biology Soultions Using R and Bioconductor. Gentleman et al. Chapter 3: Quality assessment of Affymetrix GeneChip Data, Bolstad et al.

16. Machine problems With time, settings change which reflects on the data Roos Jahangir Tafrechi Arnolda de Nooij-van Dalen old vs old new vs old