> > as.data.frame(t(sapply(splinp, function(x) summary(x
> $methylation )) ) )
>Min. 1st Qu. Median Mean 3rd Qu. Max.
> chr1 100 0.04 0.0425 0.045 0.045 0.0475 0.05
> chr1 200 0.12 0.1200 0.120 0.120 0.1200 0.12
> chr1 500 0.09 0.0900 0.090 0.090 0.090
Hello,
I have an input file that contains multiple columns, but the column I'm
concerned about looks like:
"TR"
5
0
4
1
0
2
0
To count all of the rows in the column I know how to do NROW(x$TR) which
gives 7.
However, I would also like to count only the number of rows with values >=1
(i.e. not 0
Hello,
I have an R script that I use as a template to perform a task for multiple
files (in this case, multiple chromosomes).
What I would like to do is to utilize a simple loop to parse through each
chromosome number so that I don't have to type the same code over and over
again in the R console
one file? Also, would I be able to generate one histogram from multiple
files as well (with the same format)?
For example, I have multiple files in the same format as the sample file
above, and I would like to make one histogram for all column six data in all
files.
Thank you,
a217
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Hello,
I have an input file:
http://r.789695.n4.nabble.com/file/n3700031/testOut.txt testOut.txt
where col 1 is chromosome, column2 is start of region, column 3 is end of
region, column 4 and 5 is base position, column 6 is total reads, column 7
is methylation data, and column 8 is the strand.
Yes, that is the general objective. I'll look-into aggregates in R and see if
anything helps.
Thanks,
a217
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Thank you both very much! The codes are pretty slick and should greatly help
me in my task.
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_
I have a dataframe in the general format:
chr1 0.5
chr1 0
chr1 0.75
chr2 0
chr2 0
chr3 1
chr3 1
chr3 0.5
chr7 0.75
chr9 1
chr9 1
chr22 0.5
chr22 0.5
where the first column is the chromosome location and the second column is
some value. What I'd like to do is have a histogram created for each chr
I've been looking for how to change a certain percentage of values in a data
frame, but I've been struggling to find information in R.
For example:
#example data##
> data
V1V2V3 V4 V5 V6 V7
1 chr1 500 500 CHH 0 0.5 +
2 chr1 550 550 CHH 0
I actually have two questions regarding the same script:
#
data <- vector('list', 24)
splc <- vector('list',24)
df.summ <- vector('list',24)
for (i in 1:length(chrData))
{
data[[i]] <- read.table(file=paste('chr',i,'.nonCG.covered.out',sep=''),
h
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