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Microarray Preprocessing

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Presentation on theme: "Microarray Preprocessing"— Presentation transcript:

1 Microarray Preprocessing
MBP1010H, Department of Medical Biophysics Irakli (Erik) Dzneladze

2 Affymetrix microarray processing in R

3 Affy processing pipeline
Four separate processing steps: background correction, normalization, pm correction and summary expression value computation Single Affy function runs selected algorithms in sequence

4 Step 1 - background correction
Scanner image picks up background noise in every image Background noise may be due to unbound fluorescent dyes (e.g. Cy3 and Cy5) used to label the RNA on the chip This background is quantified and subtracted from probe intensity values

5 Step 2 - normalization The hybridization step cannot be perfectly controlled. Event though RNA is quantified prior to hybridization, it is impossible to get the exact same amount of RNA to hybridize to each chip The result of this is chip to chip differences in overall distribution of probe intensity values The purpose of normalization is to minimize these systematic differences between chips so that individual chips can be compared to each other

6 Step 3 – pm correction Affymetrix GeneChips contain both perfect match (mm) and mismatch (mm) probes Mm probes quantify non-specific and cross-hybridization Originally mm signal was subtracted from pm signal to correct for non-specific and cross hybridization Many researchers prefer to ignore the mm probes entirely and use uncorrected pm probes alone

7 Step 4 – summary expression value computation
Each gene is represented by one or more probes sets Each probe set includes probe pairs Expression value for a gene is a summary of corresponding probe-level data i.e. probe level intensity values correlated with “gene expression”

8 Instructions can be found in the manual

9 Some terms used in the manual

10 Preprocessing Example Agilent Platform (Cy3 and Cy5)

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