[BioC] Illumina Custom Golden Gate Methylation. Normalization and statistics

[r.kandimalla]

Dear all,

I would like to know some information regarding normalisation and 
statistics to apply on my custom GGMA assays.

Is normalisation necessary for these assays ? if yes what do you suggest ?

I havent applied any statistics on the data to find differential 
methylation among subgroups, instead i just took the beta values and did 
comparisons. To elaborate, i have two different subgroups of tumors in 
my data set. To compare them i just took the ratio of avg beta of one 
sub groups to avg beta of another subgroup and came up with significant 
list of genes (i have chosen the ratio > 2 to be significant in that 
particular comparison).

This was a validation assay of our genome wide screen using agilent 
arrays. With custom GGMA consisting of 384 probes, we were able to 
validate quiet some data and is encouraging, but i have questions 
regarding the analysis of ggma data, whether im doing something wrong ??

Your input is highly appreciated.

Best regards,

Raju


-- 
Raju kandimalla, PhD student
Department of Pathology
Josephine Nefkens Institute
Erasmus MC, Be-302
P.O. Box 2040
3000 CA Rotterdam
The Netherlands
Tel: +31-10-7043093