# [R] find multiple mode, sorry for not providing enough information

Yuan Chun Ding ycd|ng @end|ng |rom coh@org
Mon Mar 16 23:58:18 CET 2020

```Hi Abby,

Thank you so much for your effort!! I really appreciate your help!!

I modified your code a little to get both maxv and corresponding alleles in var1.

For now, I do not care too much for identifying small peaks.

Ding

var1 <-c(1,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,20,21,22,23,24,25,31)
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)
var_freq <-data.frame(var1,freq)

temp8 <-var_freq[diff(var_freq\$freq)!=0, ]

which.maxs <- function (x, ..., include.endpoints=FALSE)
{       dx <- diff (x)
if (any (dx == 0) )
stop ("function needs unique-consecutive values")
ndx <- length (dx)
I <- c (FALSE, dx [-ndx] > 0 & dx [-1] < 0, FALSE)
if (include.endpoints)
{       I [1] <- (dx [1] < 0)
I [ndx + 1] <- (dx [ndx] > 0)
}
which (I)
}

var_freq_modes <- temp8 [which.maxs (temp8\$freq, include.endpoints=TRUE),]

-----Original Message-----
From: Abby Spurdle [mailto:spurdle.a using gmail.com]
Sent: Monday, March 16, 2020 1:57 PM
To: Yuan Chun Ding
Cc: Jim Lemon; r-help mailing list
Subject: Re: [R] find multiple mode, sorry for not providing enough information

(Sorry, that was supposed to go to the mailing list).

Here's a solution to your original question:
---------
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)

unique.consecutive <- function (x)
{       dx <- diff (x)
x [dx != 0]
}

which.maxs <- function (x, ..., include.endpoints=FALSE)
{       dx <- diff (x)
if (any (dx == 0) )
stop ("function needs unique-consecutive values")
ndx <- length (dx)
I <- c (FALSE, dx [-ndx] > 0 & dx [-1] < 0, FALSE)
if (include.endpoints)
{       I [1] <- (dx [1] < 0)
I [ndx + 1] <- (dx [ndx] > 0)
}
which (I)
}

freq.sub <- unique.consecutive (freq)
maxv <- freq.sub [which.maxs (freq.sub, include.endpoints=TRUE)]

maxv
unique (maxv)
---------

My package, probhat, contains early prototype-quality functions for discrete kernel smoothing.
This can be used to "smooth" frequency data.
Which in turn, can eliminate spurious modes.

https://urldefense.com/v3/__https://cran.r-project.org/web/packages/probhat/vignettes/probhat.pdf__;!!Fou38LsQmgU!9PTtUQp80JUeGi1gzKCC6IfoCZkZ8BO4ic42iXkMCcVlFUW4Cu1sgi1urJX0\$

Unfortunately, bandwidth selection is manual.
Also note that currently it only returns probability mass (not
frequency) but it's very easy to to get frequency from probability mass.

I'm planning to resume work on this package in two to three days, so I'm open to suggestions...

On 3/17/20, Yuan Chun Ding <ycding using coh.org> wrote:
> Hi Jim,
>
> Yes, you are right.  I sorted the tem4\$Var1 first, then find rising peaks in
> Freq variable from left to right.   I guess I probably need to define the
> minimal rising and drop on both side of a potential maxima, so avoid
> identifying really small rising peaks.  For example, I only want to
> identify the freq value of freq=10 (corresponding var1 = allele6),
> freq=8(var1=allele9),, freq=8( var1=allele12), and freq=149
> (var1=allele23),  but ignore freq=4 (var10=allele15) and freq=2 (var1=allele18).
>
> I am still working on it, any help would be really appreciated.
>
> Thank you,
>
> Ding
>
> -----Original Message-----
> From: Jim Lemon [mailto:drjimlemon using gmail.com]
> Sent: Monday, March 16, 2020 1:10 AM
> To: Yuan Chun Ding; r-help mailing list
> Subject: Re: [R] find multiple mode, sorry for not providing enough
> information
>
> [Attention: This email came from an external source. Do not open
> attachments or click on links from unknown senders or unexpected
> emails.]
>
> ----------------------------------------------------------------------
> Hi Ding,
> While I was completely off the track in my first reply, the subsequent
> posts make your problem somewhat clearer. The way you state the
> problem suggests that the order of the values of "freq" is important.
> That is, it is not just a matter of finding local maxima, but the
> direction in which you approach those maxima is important. For
> example. I might want to only identify maxima with at least four
> monotonically increasing values preceding them and a decrease of at
> least half the value of the maximum in the succeeding value. By
> breaking down the problem into a set of criteria, these can be
> implemented in a function that will search the values in one direction, returning the locations of maxima that fulfil those criteria.
>
> Jim
>
> On Mon, Mar 16, 2020 at 3:11 PM Yuan Chun Ding <ycding using 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  patients with allele 1 to allele 5 are
>> considered as carrying "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 m 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
>>
>
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