Displaying 9 results from an estimated 9 matches for "allmaf".
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allman
2017 Nov 18
3
Complicated analysis for huge databases
The loop :
AllMAFs <- list()
for (i in length(SeparatedGroupsofmealsCombs) {
AllMAFs[[i]] <- apply( SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf( tabulate( x+1) ))
}
gives these errors (I tried this many times and I'm sure I copied it entirely) :-
Error in apply(SeparatedGroupsofmealsCombs[[i...
2017 Nov 18
0
Complicated analysis for huge databases
On 18/11/2017 4:40 PM, Allaisone 1 wrote:
>
> The loop :
>
>
> AllMAFs <- list()
>
> for (i in length(SeparatedGroupsofmealsCombs) {
> AllMAFs[[i]] <- apply( SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf( tabulate( x+1) ))
> }
>
>
> gives these errors (I tried this many times and I'm sure I copied it entirely) :-
>
>...
2017 Nov 19
1
Complicated analysis for huge databases
...______________________________
From: Duncan Murdoch <murdoch.duncan at gmail.com>
Sent: 18 November 2017 23:15:15
To: Allaisone 1; David Winsemius
Cc: R-help
Subject: Re: [R] Complicated analysis for huge databases
On 18/11/2017 4:40 PM, Allaisone 1 wrote:
>
> The loop :
>
>
> AllMAFs <- list()
>
> for (i in length(SeparatedGroupsofmealsCombs) {
> AllMAFs[[i]] <- apply( SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf( tabulate( x+1) ))
> }
>
>
> gives these errors (I tried this many times and I'm sure I copied it entirely) :-
>
> Er...
2017 Nov 18
0
Complicated analysis for huge databases
...ataframes
>
>
> ________________________________
> From: Boris Steipe <boris.steipe at utoronto.ca>
> Sent: 18 November 2017 00:35:16
> To: Allaisone 1; R-help
> Subject: Re: [R] Complicated analysis for huge databases
>
> Something like the following?
>
> AllMAFs <- list()
>
> for (i in length(SeparatedGroupsofmealsCombs) {
> AllMAFs[[i]] <- apply( SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf( tabulate( x+1) ))
> }
>
>
> (untested, of course)
> Also the solution is a bit generic since I don't know what the outpu...
2017 Nov 18
2
Complicated analysis for huge databases
...9
.
.
~180 dataframes
________________________________
From: Boris Steipe <boris.steipe at utoronto.ca>
Sent: 18 November 2017 00:35:16
To: Allaisone 1; R-help
Subject: Re: [R] Complicated analysis for huge databases
Something like the following?
AllMAFs <- list()
for (i in length(SeparatedGroupsofmealsCombs) {
AllMAFs[[i]] <- apply(SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf(tabulate(x+1)))
}
(untested, of course)
Also the solution is a bit generic since I don't know what the output of maf() looks like in your case, and I d...
2017 Nov 18
0
Complicated analysis for huge databases
The correct code is:
for (i in 1:length(SeparatedGroupsofmealsCombs)) { ...
I had mentioned that this is untested, but the error is so obvious ...
B.
> On Nov 18, 2017, at 4:40 PM, Allaisone 1 <allaisone1 at hotmail.com> wrote:
>
>
> The loop :
>
> AllMAFs <- list()
>
> for (i in length(SeparatedGroupsofmealsCombs) {
> AllMAFs[[i]] <- apply( SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf( tabulate( x+1) ))
> }
>
> gives these errors (I tried this many times and I'm sure I copied it entirely) :-
> Error in ap...
2017 Nov 18
0
Complicated analysis for huge databases
Something like the following?
AllMAFs <- list()
for (i in length(SeparatedGroupsofmealsCombs) {
AllMAFs[[i]] <- apply(SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf(tabulate(x+1)))
}
(untested, of course)
Also the solution is a bit generic since I don't know what the output of maf() looks like in your case, and I d...
2017 Nov 18
2
Complicated analysis for huge databases
Thanks Boris , this was very helpful but I'm struggling with the last part.
1) I combined the first 2 columns :-
library(tidyr)
SingleMealsCode <-unite(MyData, MealsCombinations, c(MealA, MealB), remove=FALSE)
SingleMealsCode <- SingleMealsCode[,-2]
2) I separated this dataframe into different dataframes based on "MealsCombination"
column so R will recognize each meal
2017 Nov 17
0
Complicated analysis for huge databases
Combine columns 1 and 2 into a column with a single ID like "33.55", "44.66" and use split() on these IDs to break up your dataset. Iterate over the list of data frames split() returns.
B.
> On Nov 17, 2017, at 12:59 PM, Allaisone 1 <allaisone1 at hotmail.com> wrote:
>
>
> Hi all ..,
>
>
> I have a large dataset of around 600,000 rows and 600