normalization and clustering etc...
0
0
Entering edit mode
@phguardiolaolcom-152
Last seen 10.2 years ago
Hi all, I have recently discover Cyber-T and I was wondering if this Bayesian approach for comparison was available in Bioconductor since I dont always have a fast internet connection and I m not working on Unix / Linux yet ? What seems to be a similar approach is apparently available in the new S+ module Array analyzer is it also in R/Bioconductor ? In the same way, is there any kind of Bayesian clustering method available in Bioconductor like the one available in Array Miner ? In addition, I have two questions that I d like to have some help about from your group: I ve affy 133A+B chips made from RNA coming from 4 cell lines. Two of these cell lines are B cells (one has a deficient gene and the other has the corrected gene inserted instead of the deficient one, both are coming from the same parental cell line) and 2 others are fibroblastic cell lines in which the same gene is inactivated or not. Therefore I have 2 cell lines deficient for a gene C (one fibroblast one B cell) and their corrected homologs. In addition, all these cells have been exposed to the same chemotherapeutic agent at the same dose same duration so that I have data from untreated and treated cells. I am planning to compare corrected versus uncorrected untreated B cells, then the same for fibroblasts, then all this again for treated cells. The aim is to isolate genes that are differentially expressed in nornal conditions between the deficient and corrected B cells then the same for the fibroblasts and then finally to see which one are in both cases differentially expressed. Finally I d like to know what are the modifications of these results when I stress the cells with chermo. So here are my qurestions: - For normalization: should I normalize the whole set of chips then do all my comparisons or should I normalize only the chips I am planning to compare at each time and repeat this process for each comparison ? I m planning to use the RMA module. - For clustering: I have identified at least one gene W of great interest in my model and I was planning to do clustering analysis to see what are the genes with a similar pattern of expression. Using all my differents conditions with my 4 cell lines I found one very interesting gene Z in the cluster of the first gene W. I was wondering if it would be a good idea to add some extra chips made from completely different cells, ie, CD34+ hematopoietic stem cells, mature Cd22+ B cells, acute leukemia cell lines in my case, as a validation process ? For instance, if the gene Z is not anymore close to gene W with these extra chips... what could be the conclusion...? Thanks for your help Philippe [[alternate HTML version deleted]]
Bayesian Clustering Leukemia affy PROcess DOSE Bayesian Clustering Leukemia affy PROcess • 1.1k views
ADD COMMENT

Login before adding your answer.

Traffic: 442 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6