Introduction to Microarray analysis

Overview of experimental process

File:Expt2.tiff

• Competitive hybridization to spotted oligo/cDNA transcripts
• Interested in genes that change between treatment conditions

→ differential expression versus equivalent expression

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Statistical analysis process

File:Overview2.tiff

• Raw data (GPR file format)

http://www.moleculardevices.com/pages/software/gn_gpr_format_history.html

• Each GPR intensity file is typically >8 megabytes
• Each TIFF image file is typically >30 megabytes
• A microarray experiment consists of several → many slides

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Statistical issues

• In the past statistics was developed for n >>p

n observations, p variables

• Gene expression data n<<p

Thousands of measured genes (p)

Small number of biological replicate slides (n)

• Gene expression data can be highly correlated

groups of genes are regulated in the same way

• Data not normally distributed

log transform highly skewed intensity data

File:Graph channels.tiff

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Analysis wish list

• Ideally would like unambiguous interpretation of results
• Large amounts of data to analyse can be overwhelming and make interpretation subjective
• Independent reproducibility of results by another collegue

→Keep a record (log) of what was done

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Analysis aim

• Easier to rank genes in order of evidence of differential expression than it is to select a specific cutoff
• If we do select a cutoff, False Discovery Rate (FDR) cutoff is usually used

FDR threhold is the expected proportion of genes in a list that are likely to be incorrect

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