On 12/3/19 12:16 PM, Ana Marija wrote:
would this make sense for the previous:
mt=na.omit(m, cols = c("V1.1","V1.2","V1.3","V1.4","V1.5"))
On Tue, Dec 3, 2019 at 2:09 PM Ana Marija
wrote:
I can perhaps do this:
m=Reduce(function(x, y) merge(x, y, all=TRUE), list(s11, s22, s33,s44,s55))
bu
I apologize I would need to reformulate this problem because there will be
much more unique genes I have to look up, 381
so all genes or in one data frame
> head(r)
V1 V2 V3V4
1 ENSG0273172 rs7215271 4.33932e-17 -0.602316
2 ENSG0273172 rs34889101 4
would this make sense for the previous:
mt=na.omit(m, cols = c("V1.1","V1.2","V1.3","V1.4","V1.5"))
On Tue, Dec 3, 2019 at 2:09 PM Ana Marija
wrote:
> I can perhaps do this:
>
> m=Reduce(function(x, y) merge(x, y, all=TRUE), list(s11, s22, s33,s44,s55))
>
> but than in the output of this one SNP
I can perhaps do this:
m=Reduce(function(x, y) merge(x, y, all=TRUE), list(s11, s22, s33,s44,s55))
but than in the output of this one SNP (just for example)
> head(m)
rsV1.1V3.1 V4.1 V1.2 V3.2 V4.2
V1.3
6 rs1029829 ENSG0154803 1.02519e-11 0.469402NA NA
the desired output would look like this (example give just for two genes,
it should include all 5 from all 5 data frames):
where the example is if say only 5 rs are shared between those two genes,
what is given after rs# is values from V4 column for each gene
GENES ENSG0001629 ENSG0127914
Hello,
I have 5 dataframes (s11,s22,s33,s44,s55) that look like this:
> head(s11)
V1.1 rs V3.1V4.1
1 ENSG0154803 rs12940868 3.80175e-05 -0.519565
2 ENSG0154803 rs4383187 8.92772e-05 -0.367303
3 ENSG0154803 rs4404112 9.32402e
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