# [R] how to calculate multiple meta p values

Ana Marija @okov|c@@n@m@r|j@ @end|ng |rom gm@||@com
Mon Oct 28 20:06:25 CET 2019

```Hi Michael,

I tried what you proposed with my data frame 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

Ana

On Sun, Oct 27, 2019 at 9:49 AM Michael Dewey <lists using dewey.myzen.co.uk> wrote:
>
> Dear Ana
>
> There must be several ways of doing this but see below for an idea with
>
> 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
> >            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
> >
> >         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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