Hi Jim, Thanks very much for the reply. phenoTest looks for univariate assocations- i.e. it tests variables one-by-one using Limma, so in this case I have many tests and I guess I will have to correct appropriately. Regards, Jon On 14/01/2013 15:09, James W. MacDonald wrote: > Hi Jon, > > On 1/14/2013 7:07 AM, Jon Manning wrote: >> Hi Bioconductors, >> >> I'm using the phenoTest package to look for associations between >> various continuous and categorical clinical variables and methylation >> values stored in an eset-like object. >> >> As suggested I apply the BH method to correct for multiple testing >> probe-wise. However, as I understand it this does not account for >> variable-wise multiple testing, and with my collaborator introducing >> many new variables I'm concerned this will create unnecessary >> spurious associations. >> >> So the question is simple: should I just do a simple column >> (variable)-wise bonferroni correction, after the row (probe) -wise BH >> correction? > > Adding more variables to the model doesn't increase the number of > tests, but doing more tests does. In other words, if you are fitting > multiple models, then you are increasing the number of tests, but > simply adding a new variable to an existing model doesn't increase > multiplicity (as long as you only use your final model). > > Best, > > Jim > > >> >> All pointers appreciated, >> >> Regards, >> >> Jon Manning >> > -- Dr Jonathan Manning Bioinformatics Team Centre for Cardiovascular Science University of Edinburgh Queens Medical Research Institute 47 Little France Crescent Edinburgh EH16 4TJ United Kingdom T: +44 131 242 6700 F: +44 131 242 6782 E: jmanning at staffmail.ed.ac.uk The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.