comparison of R/Bioconductor microarray analysis with other statistical tools

[maembe]

Hey,

Am new here, so i think its appropriate to say a humble hallo..

secondly, am also new to bioinformatics but i have managed to do some analysis in the past few weeks. my main aim was to compair two groups of patients to determine genes which were differentially expressed from the two groups. i did the analysis on Pertek and also on R/Bioconductor.
am however observing something wierd; the results are not comparable. I'm getting more genes when using the commercial software compared to when i use R/bioconductor.

Can someone give me a heads up on what might be going on here..

[GenoMax]

That is not entirely unexpected unless the difference in numbers you are observing is very large.

Have you compared the exact methods that the partek analysis used with the R/bioconductor? Even then there may be subtle differences in how a method is coded in software.

[maembe]

Pertek uses ANOVA to determine all differentially expressed genes, by calculating the F-statistics critical value. On the other hand, for R/Bioconductor, i used DEGexp function, in the DEGseq library to get my gene list. Now, i acheved this by splitting the whole dataset containing gene expression values into two groups then loaded them onto DEGexp funtion. I am not sure if it can be considered as the correct approach.

with R/Bioconductor, i could only get 200 genes at a p-value of 0.05, yet Pertek gave me close to 5000 genes.I'm totally confused since i dont know which results to trust

Your comments will be appreciated
Kind regards