Visualisation and pre-processing of peptide microarray data.
The data files produced by digitising peptide microarray images contain detailed information on the location, feature, response parameters and quality of each spot on each array. In this chapter, we will describe how such peptide microarray data can be read into the R statistical package and pre-processed in preparation for subsequent comparative or predictive analysis. We illustrate how the information in the data can be visualised using images and graphical displays that highlight the main features, enabling the quality of the data to be assessed and invalid data points to be identified and excluded. The log-ratio of the foreground to background signal is used as a response index. Negative control responses serve as a reference against which "detectable" responses can be defined, and slides incubated with only buffer and secondary antibody help identify false-positive responses from peptides. For peptides that have a detectable response on at least one subarray, and no false-positive response, we use linear mixed models to remove artefacts due to the arrays and their architecture. The resulting normalized responses provide the input data for further analysis.
Reilly
Marie
M
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Valentini
Davide
D
D000818:Animals; D019295:Computational Biology / Q000379:methods; D001330:Electronic Data Processing / Q000379:methods*; D005189:False Positive Reactions; D005544:Forecasting; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019151:Peptide Library; D040081:Protein Array Analysis / Q000295:instrumentation / Q000379:methods*; D011786:Quality Control
D019151:Peptide Library