End of project reportDNA microarrays are widely used for gene expression profiling. Raw data resulting from microarray experiments, however, tends to be very noisy and there are many sources of technical variation and bias. This raw data needs to be quality assessed and interactively preprocessed to minimise variation before statistical analysis in order to achieve meaningful result. Therefore microarray analysis requires a combination of visualisation and statistical tools, which vary depending on what microarray platform or experimental design is used.Bioconductor is an existing open source software project that attempts to facilitate
analysis of genomic data. It is a collection of packages for the statistical programming
language R. Bioconductor is particularly useful in analyzing microarray experiments. The
problem is that the R programming language’s command line interface is intimidating to
many users who do not have a strong background in computing. This often leads to a
situation where biologists will resort to using commercial software which often uses
antiquated and much less effective statistical techniques, as well as being expensively
priced. This project aims to bridge this gap by providing a user friendly web-based
interface to the cutting edge statistical techniques of Bioconductor
