Can you please get back to me about this, I need this meta p values
for manuscript I have to submit next week
On Wed, Oct 30, 2019 at 5:35 PM Ana Marija wrote:
>
> I also tried to do it this way:
>
> d$META <- sapply(seq_len(nrow(d)), function(rn) {
> unlist(sumz(as.matrix(d[,.(LCL,Retina)])[rn
I also tried to do it this way:
d$META <- sapply(seq_len(nrow(d)), function(rn) {
unlist(sumz(as.matrix(d[,.(LCL,Retina)])[rn,], weights =
as.vector(d[,.(wl,wr)])[rn,],
na.action=na.fail)["p"])
})
but again I am getting error:
Error in sumz(as.matrix(d[, .(LCL, Retina)])[rn, ], we
Hi Michael,
this still doesn't work, by data frame has a few less columns now, but
the principle is still the same:
> head(d)
chrpos gene_id LCL
Retina wl wr
1: chr1 775930 ENSG0237094 0.3559520 9.72251e-05 31.62278 21.2838
2: chr1 815963 EN
Dear Ana
Yes, when apply coerces q to a matrix it does so as a character matrix
because of the values in the first column. So you need to wrap the
references to x in helper in as.numeric() tat is to day like
as.numeric(x[2:4]) and similarly for the other one. Sorry about that, I
should have t
Hi Michael,
I tried what you proposed with my data frame q:
> head(q)
IDP G E
wb wg we
1: rs1029830 0.0979931 0.0054060 0.39160 580.6436 40.6325 35.39774
2: rs1029832 0.1501820 0.0028140 0.39320 580.6436 40.6325 35.39774
3:
Dear Ana
There must be several ways of doing this but see below for an idea with
comments in-line.
On 26/10/2019 00:31, Ana Marija wrote:
Hello,
I would like to use this package metap
to calculate multiple o values
I have my data frame with 3 p values
head(tt)
RSG
this is the function I was referring to:
https://www.rdocumentation.org/packages/metap/versions/1.1/topics/sumz
On Fri, Oct 25, 2019 at 6:31 PM Ana Marija wrote:
>
> Hello,
>
> I would like to use this package metap
> to calculate multiple o values
>
> I have my data frame with 3 p values
> > hea
Hello,
I would like to use this package metap
to calculate multiple o values
I have my data frame with 3 p values
> head(tt)
RSG E B
1: rs2089177 0.9986 0.7153 0.604716
2: rs4360974 0.9738 0.7838 0.430228
3: rs6502526 0.9744 0.7839 0.4291
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