Not getting Adjusted p-values from multtest package
1
0
Entering edit mode
elhananby ▴ 10
@elhananby-9276
Last seen 9.0 years ago

Hello everybody,

I'm trying to run an analysis on methylation percentage using the multtest package, but I'm running into a problem.

I have a matrix where each columns is a subject, and each row is a number between 0-100, corresponding to percentage of methylation at that specific loci on the genome. Further, i have a vector containing the groups coding, so '0' represent a control and '1' a case.

I'm trying to run a t-test between the two groups (cases and controls) using the mt.maxT function, and while I'm getting the t-values and raw-p-values, all of the values in the adjusted p-value (adjp) are 1.

I'm trying to run the function as so:

mt.maxT(methyl.matrix, coding_groups, test = "t", side ="abs", fixed.seed.sampling = "y", B = 1000)

I've tried to run the raw p-values through the mt.rawp2adjp function, but then I'm getting an adjusted p list of 1s and 0s.

Furthermore, when trying to run the analysis using the MTP function, i'm getting this error:

Only one unique value in bootstrap sample for first group. Cannot calculate variance. This problem may be resolved if you try again with a different seed.

This error remains even after removing all missing (NA) values list-wise.

 

Any help will be appreciated, 

Thanks.

multtest methylation adjusted pvalue • 1.4k views
ADD COMMENT
1
Entering edit mode
kpollard ▴ 110
@kpollard-7578
Last seen 9.4 years ago
United States
It sounds like you have a lot of hypotheses and that after multiple testing adjustment all non-zero unadjusted p-values become 1s, which is probably the correct output of the maxT procedure. It is designed to control family-wise error, so will increase p-values a great deal when you have many tests. The function mt.rawp2adjp with proc=�BH� (or �BY�, �ABH�, or �TSBH�) will allow you to control FDR, which might be more satisfying in your scenario. This still may produce many 1s if you have a large number of tests and there are no significant differences. Best, Katie On Nov 26, 2015, at 4:59 AM, elhananby [bioc] <noreply@bioconductor.org> wrote: > Activity on a post you are following on support.bioconductor.org > User elhananby wrote Question: Not getting Adjusted p-values from multtest package: > > > Hello everybody, > > I'm trying to run an analysis on methylation percentage using the multtest package, but I'm running into a problem. > > I have a matrix where each columns is a subject, and each row is a number between 0-100, corresponding to percentage of methylation at that specific loci on the genome. Further, i have a vector containing the groups coding, so '0' represent a control and '1' a case. > > I'm trying to run a t-test between the two groups (cases and controls) using the mt.maxT function, and while I'm getting the t-values and raw-p-values, all of the values in the adjusted p-value (adjp) are 1. > > I'm trying to run the function as so: > > mt.maxT(methyl.matrix, coding_groups, test = "t", side ="abs", fixed.seed.sampling = "y", B = 1000) > I've tried to run the raw p-values through the mt.rawp2adjp function, but then I'm getting an adjusted p list of 1s and 0s. > > Furthermore, when trying to run the analysis using the MTP function, i'm getting this error: > > Only one unique value in bootstrap sample for first group. Cannot calculate variance. This problem may be resolved if you try again with a different seed. > This error remains even after removing all missing (NA) values list-wise. > > > Any help will be appreciated, > > Thanks. > > > Post tags: multtest, methylation, adjusted pvalue > > You may reply via email or visit Not getting Adjusted p-values from multtest package >
ADD COMMENT

Login before adding your answer.

Traffic: 558 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