Identifying which pairs of individuals were clones in the data

[sho...@mortonarb.org]

I am able to successfully use poppr (function clonecorrect) for counting and removing clones from my dataset.  However I want to identify which pairs/groups were the clones. I.e. for those removed, which remaining individuals they matched to.  I want to do this so I can measure geographic distance between individuals that turned out to be clones.

[Zhian Kamvar]

Hi Sean,

You can use the `mlg.id()` function to extract this information on the full (not clone-corrected) data set. It will return a list where each element represents a genotype and contains a vector of sample names. You can use this list to subset a data frame of geographic coordinates. See the example below.

library("poppr")

data(monpop)

show(monpop)

#> 

#> This is a genclone object

#> -------------------------

#> Genotype information:

#> 

#>    264 multilocus genotypes 

#>    694 haploid individuals

#>     13 codominant loci

#> 

#> Population information:

#> 

#>      1 stratum - Pop

#>     12 populations defined - 

#> 7_09_BB, 26_09_BB, 26_09_FR, ..., 45_10_FR, 26_11_BB, 26_11_FR

#

# Filter the data to collapse all genotypes that are different by 

# at most one mutation

e <- .Machine$double.eps^0.5

mlg.filter(monpop) <- 1 + e

show(monpop)

#> 

#> This is a genclone object

#> -------------------------

#> Genotype information:

#> 

#>    190 contracted multilocus genotypes

#>        (1) [t], (diss.dist) [d], (farthest) [a] 

#>    694 haploid individuals

#>     13 codominant loci

#> 

#> Population information:

#> 

#>      1 stratum - Pop

#>     12 populations defined - 

#> 7_09_BB, 26_09_BB, 26_09_FR, ..., 45_10_FR, 26_11_BB, 26_11_FR

#

# The `mll()` function will list the multilocus genotype/lineage

# assignment per sample.

mll(monpop)[10:19] # Samples 10, 11, and 12 are all part of the same clone

#>  [1]  79  79  79  81 130  41  41  41  38 119

indNames(monpop)[10:19]

#>  [1] "A021" "A022" "A007" "A001" "A018" "A020" "A017" "A019" "A003" "A005"

#

# mlg.id will identify them. 

mlg.id(monpop)[["79"]] # MLL 79 contains four clones

#> [1] "A021" "A022" "A007" "A033"

#

# Using this with a 2-column data frame of geographic coordinates 

meandist <- function(i, df) mean(dist(df[i, , drop = FALSE]))

df  <- data.frame(x = rnorm(nInd(monpop)), 

                  y = rnorm(nInd(monpop)), 

                  row.names = indNames(monpop))

# Coordinates can be identified for MLL 79

ids <- mlg.id(monpop)

df[ids[["79"]], , drop = FALSE]

#>               x          y

#> A021 -0.5901603 -0.5354590

#> A022 -1.2622871  0.9373863

#> A007  0.3141743 -1.3958612

#> A033 -1.5612730 -1.2284351

#

# loop over the list to calculate mean distance

res        <- vapply(mlg.id(monpop), FUN = meandist, FUN.VALUE = numeric(1), df)

names(res) <- names(mlg.id(monpop))

res[["79"]]

#> [1] 1.82423

Created on 2018-04-13 by the [reprex package](http://reprex.tidyverse.org) (v0.2.0).

-----

Zhian N. Kamvar, Ph. D.

Postdoctoral Researcher (Everhart Lab)

Department of Plant Pathology

University of Nebraska-Lincoln

ORCID: 0000-0003-1458-7108

On Apr 13, 2018, at 11:46 , sho...@mortonarb.org wrote:

I am able to successfully use poppr (function clonecorrect) for counting and removing clones from my dataset.  However I want to identify which pairs/groups were the clones. I.e. for those removed, which remaining individuals they matched to.  I want to do this so I can measure geographic distance between individuals that turned out to be clones.

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[sho...@mortonarb.org]

Thank you!  This worked out perfectly.  Thanks for sample code