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 thought of it before.
When I next update metap I will try to get it to degrade more gracefully
when it finds an error.
Michael
On 28/10/2019 19:06, Ana Marija wrote:
Hi Michael,
I tried what you proposed with my data frame q:
head(q)
ID P 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: rs11078374 0.1701250 0.0009805 0.49730 580.6436 40.6325 35.39774
4: rs1124961 0.1710150 0.7252000 0.05737 580.6436 40.6325 35.39774
5: rs1135237 0.1493650 0.6851000 0.06354 580.6436 40.6325 35.39774
6: rs11867934 0.0757972 0.0006140 0.00327 580.6436 40.6325 35.39774
so the solution of the first row would be this:
sumz(c(0.0979931,0.0054060,0.39160), weights = c(580.6436,40.6325,35.39774),
na.action = na.fail)
sumz = 1.481833 p = 0.06919239
I tried applying the function you wrote:
helper <- function(x) {
p <- sumz(x[2:4], weights = x[5:7])$p
p
}
With:
q$META <- apply(q, MARGIN = 1, helper)
# I want to make a new column in q named META with results
but I got this error:
Error in sumz(x[2:4], weights = x[5:7]) :
Must have at least two valid p values
Please advise,
Ana
On Sun, Oct 27, 2019 at 9:49 AM Michael Dewey <li...@dewey.myzen.co.uk> wrote:
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)
RS G E B
1: rs2089177 0.9986 0.7153 0.604716
2: rs4360974 0.9738 0.7838 0.430228
3: rs6502526 0.9744 0.7839 0.429160
4: rs8069906 0.7184 0.4918 0.521452
5: rs9905280 0.7205 0.4861 0.465758
6: rs4313843 0.9804 0.8522 0.474313
and data frame with corresponding weights for each of the p values
from the tt data frame
head(df)
wg we wb RS
1 40.6325 35.39774 580.6436 rs2089177
2 40.6325 35.39774 580.6436 rs4360974
3 40.6325 35.39774 580.6436 rs6502526
4 40.6325 35.39774 580.6436 rs8069906
5 40.6325 35.39774 580.6436 rs9905280
6 40.6325 35.39774 580.6436 rs4313843
RS column is the same in df and tt
So you can create a new data-frame with merge()
newdata <- merge(tt, df)
which will use RS as the key to merge them on.
The write a function of one argument, a seven element vector, which
picks out the p-values and the weights and feeds them to sumz().
Something like
helper <- function(x) {
p <- sumz(x[2:4], weights = x[5:7])$p
p
}
Note you need to check that 2:4 and 5:7 are actually where they are in
the row of newdat.
Then use apply() to apply that to the rows of newdat.
I have not tested any of this but the general idea should be OK even if
the details are wrong.
Michael
How to use this sunz() function to create a new data frame which would
look the same as tt only it would have additional column, say named
"META" which has calculated meta p values for each row
This i s example of how much would be p value in the first row:
sumz(c(0.9986,0.7153,0.604716), weights = c(40.6325,35.39774,580.6436),
na.action = na.fail)
p = 0.6940048
Thanks
Ana
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--
Michael
http://www.dewey.myzen.co.uk/home.html
--
Michael
http://www.dewey.myzen.co.uk/home.html
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
