How does SNP work?

1. In coding region of gene, if the SNP result in a non-synonymous mutation it would change the translated protein structure and function.
2. In coding region of gene, if the SNP is a synonymous mutation, the translated protein sequence might not be changed. But it is very interesting that the structure of protein would still have probabilty to be changed [17185560].

3. In promoter region, it would change the expression pattern of downstream genes[17053109 , 17053108].
4. In intron, ???
5. In other region, ???

Standard procedure in R for pre-processing of Affy .CEL file

Modified from Soumyaroop Bhattacharya (sbhattacharya@rics.bwh.harvard.edu) 's post at http://lungtranscriptome.bwh.harvard.edu/Microarray%20Data%20Analysis%20using%20Bioconductor.pdf .

Using affy package
Save all the .CEL files for the analysis and the corresponding .CDF file for the particular array in one directory. If you are connected to internet then R will get .CDF file. Run R from that irectory.
In R write

• library (affy)
• Data <- ReadAffy() # Reads in Data

Then creating Expression Intensity Values by one of the following ways:

1. RMA

• eset <- rma(Data)
  

OR

• eset <- expresso (Data, normalize.method=”quantile.robust”, bgcorrect.method=”rma”, pmcorrect.method=”pmonly”,summary.method=”medianpolish”)
• write.exprs(eset,file=”myDataRMA.txt”)

2. DChip

• eset <- expresso (Data, normalize.method=”invariantset”, bgcorrect=FALSE, pmcorrect.method=”pmonly”, summary.method=”liwong”)

• write.exprs(eset,file=”myDataDChip.txt”)

3. MAS 5.0 Expression Intensities (http://www.affymetrix.com/analysis)

• eset <- mas5(Data)

OR

• eset <- expresso (Data, normalize =FALSE, bgcorrect.method=”mas”, pmcorrect.method=”mas”, summary.method=”mas”)
  

• write.exprs(eset,file=”myDataMAS5.txt”)

• Calls <- mas5calls(Data)