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There are currently a few bioinformatics tools, such as dbEST, DDD, GEPIS, cDNA xProfiler and cDNA DGED to name a few, which have been widely used to retrieve and analyse EST expression data and for comparing gene expression levels e.g. between cancer and normal tissues. The outcome of any such comparison depends on EST libraries' annotations and assumes that the actual expression data (EST counts) are correct. None of the existing tools provide a quality control method for the selection and evaluation of the original EST expression libraries. Here we report the selection, optimisation and evaluation of a minimal gene expression data set using CGAP cDNA DGED. Our approach relies solely on the expression data itself and is independent on the libraries annotations. The reported approach allows tissue typing of expression libraries of different sizes containing between as little as 249 total EST counts and up to 13,929 total EST counts (the highest tested so far).

Optimisation and Validation of a Minimum Data Set for the Identification and Quality Control of EST Expression Libraries