You **might** do better pursuing this sort of thing on the Bioconductor site:
https://www.bioconductor.org/help/<https://urldefense.com/v3/__https://www.bioconductor.org/help/__;!!Fou38LsQmgU!441uqddHFvpuq6wfAy-jNNUZ8Dz_jGxN9itKerhoPxav-yjaqUkpwPhN4bJJ$>
They often have professionally written R packages tailored for genomics so that
you don't need to shake and bake your own with all the dangers that entails
(not least of which may be that your methodology is suspect).
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
Thank you, Bert!
I just realized that I made a typo in the following email, so I modified it
using the red font. we are doing genomics work, but this is a understudied
genomic research, so no professional packages. I admit that what I am doing is
pretty explorative.
On Sun, Mar 15, 2020 at 9:11 PM Yuan Chun Ding
<ycd...@coh.org<mailto:ycd...@coh.org>> wrote:
sorry, I just came back.
Yes, Abby's understanding is right.
> tem4$Var1
[1] 1 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 20
21 22 23 24 25 31
> tem4$Freq
[1] 1 2 5 5 10 4 4 8 1 1 8 8 2 4 3 1
2 1 1 138 149 14 1 1
I have 2000 markers, this is just one example marker, the var1 is a VNTR marker
with alleles 1, 3, 4 etc, a multi-allele marker; the corresponding frequency
for each allele is 1,2 5 etc. I want to convert this multi-allele marker to
bi-allele markers by choosing a cutoff value; I would want the cut point to be
allele 6 with frequency of 10, so allele 1 to allele 5 are considered as
"short" allele, allele 6 to 31 as "long" allele; then sliding to next rsing
frequency peak, allele 8 with frequency of 8, etc.
maybe those rising peaks are not really multiple modes, but I want to do this
type of data conversion. I want to first determine the number of modes, then
convert input dat file into m different input files, then perform Cox
regression analysis for each converted file. I am stuck in the step of find out
m rise peaks.
Thank you,
Ding
tem <- as.data.frame(t(dat[i,,drop=F]))
names(tem)<-"V1"
tem <- tem[which(tem$V1!=""),,drop=F]
tem2 <-separate(tem, col=V1, into=c("m1","m2"), convert = T)
tem3 <-gather(tem2, marker, VNTR_repeats, m1:m2)
tem4 <-as.data.frame(t(t(table(tem3$VNTR_repeats))))[,c(1,3)]
tem4$Var1 <-as.numeric(as.character(tem4$Var1))
tem4 <-tem4[order(tem4$Var1),]
m<-
________________________________________
From: Abby Spurdle [spurdl...@gmail.com<mailto:spurdl...@gmail.com>]
Sent: Sunday, March 15, 2020 3:42 PM
To: Jim Lemon
Cc: Yuan Chun Ding; r-help mailing list
Subject: Re: [R] find multiple mode
I think people have misinterpreted the question.
The OP wants local maxima from the series.
The original series is frequencies, so your table is frequencies of frequencies.
A solution can be derived by looking at signs of the first and second
differences.
But there may be a simpler way????
On Mon, Mar 16, 2020 at 10:24 AM Jim Lemon
<drjimle...@gmail.com<mailto:drjimle...@gmail.com>> wrote:
>
> Hi Ding,
> Translating this into R code:
>
> freq<-c(1,2,5,5,10,4,4,8,1,1,8,8,2,4,3,1,2,1,1,138,149,14,1,1)
> > table(freq)
> freq
> 1 2 3 4 5 8 10 14 138 149
> 8 3 1 3 2 3 1 1 1 1
> > library(prettyR)
> > Mode(freq)
> [1] "1"
>
> You have a single modal value (1). If there were at most two ones, you
> would have three values (2,4,8) that could be considered multiple
> modes. What you seem to be doing is considering values that are not
> separated by commas as modes. Perhaps this is a formatting problem
> with your email.
>
> Jim
>
> On Mon, Mar 16, 2020 at 7:55 AM Yuan Chun Ding
> <ycd...@coh.org<mailto:ycd...@coh.org>> wrote:
> >
> > Hi R users,
> >
> > I want to find multiple modes (10, 8, 149) for the following vector.
> >
> > freq =1,2,5,5 10,4,4,8,1,1,8,8,2,4,3,1,2,1,1 138 149 14,1,1;
> >
> > any suggestion?
> >
> > Thank you,
> >
> > Ding
> >
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