Dear Pia, to supplement Sean's suggestion, you could look at the two papers cited here: http://www.ebi.ac.uk/huber-srv/queryGene The analysis for this project was done with the tilingArray package. But applying this to your data will require a substantial amount of your own programming, due to the variety of tasks, the tilingArray package does not provide an easy to use end-to-end it solution; just some buiding blocks. Still, of course, I hope that it is useful, let me know if you have questions. Best wishes Wolfgang ------------------------------------------------------------------ Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber Sean Davis ha scritto: > Pia Sappl wrote: >> Dear Tiling Array Users >> >> We have recently performed an Arabidopsis Tiling Array experiment to >> assess differential expression between mock treated and dex treated >> samples at 4 and 12 h after dex treatment (2 biological paired >> replicates = 8 chips in total). ie mock 4h versus dex 4 h and mock 12 h >> vs dex 12 h. As part of our analysis we would like to identify regions >> of DNA that do not fall within annotated exons (ie unannotated genes). >> Is anyone aware of an existing R algorithm we could use (or perhaps with >> minimal modifications) that would do this? So far we have used TAS >> (Affymetrix software) to normalise the data and define regions of >> positive expression. We have also used IGB (Affymetrix genome browser) >> to manually inspect the results. However, we would like to take a more >> automated and objective approach using R. Finally, has anyone used the >> Tiling Array to identify differential expression? And if so, what >> approach was used? >> > I haven't used the package in a long time, but you might look at the > tilingArray package. Also, I would highly recommend reading some of the > literature utilizing tiling arrays. The analysis of such arrays is full > of challenges and will probably require some customized analyses to > answer specific biologic questions. >