Some code to cut and paste would be helpful. The following may help out.
library(multtest)
# create some p-values
p <- runif(100)
p <- sort(p)
p_adj <- mt.rawp2adjp(p, proc="BH", alpha = 0.05)
> str(p_adj)
List of 4
$ adjp : num [1:100, 1:2] 0.0142 0.0174 0.0254 0.0258 0.0736 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr [1:2] "rawp" "BH"
$ index : int [1:100] 1 2 3 4 5 6 7 8 9 10 ...
$ h0.ABH : NULL
$ h0.TSBH: NULL
> p_results <- p_adj$adjp
> is.data.frame(p_results)
[1] FALSE
p_results <- as.data.frame(p_results)
p_results[p_results$BH < 0.8,]
p_subset <- subset(p_results,BH < 0.8)
On Tue, Mar 2, 2010 at 11:04 PM, Sahil Seth <sahiilseth at gmail.com>
wrote:> Hello R experts,
> I am trying to analyze this dataset and am stuck on this problem for quite
> some time now.
> I am using mt.rawp2adjp.
> the output that came out was a matrix with two colums since I had asked it
> to calculate the adjusted p values using one method.
> so it has the two columns as: rawp BH
>
> I combined these using cbind with my actual dataframe.
> checked using head all was fine.
>
> thereafter I am trying to extract the rows where the values in BH are below
> a particular value(alpha say 0.05):
> by the command:
> partMult <- subset(multData,BH < 0.05)
> this gives a error saying that
> the operator < is not valid for factors.
> Initally it seemed that the column BH is a factor, but typeof(BH) revealed
> that it is a integer variable.
>
> I also tried converting it into doube, and it did convert but then the
> values just changed:
> 0.0008 became 34
> .0009 become say 28 and so on.
>
> It would be great to have your inputs on the issue.
>
> I am currently exploring the mt.reject function.
>
> thanks
> Sahil
>
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