View source: R/getAssignable.R
getAssignCat | R Documentation |
Identify which individuals are SNP genotyped, and which can potentially be substituted by a dummy individual ('Dummifiable').
getAssignCat(Pedigree, SNPd, minSibSize = "1sib1GP")
Pedigree |
dataframe with columns id-dam-sire. Reference pedigree. |
SNPd |
character vector with ids of genotyped individuals. |
minSibSize |
minimum requirements to be considered 'dummifiable':
. |
It is assumed that all individuals in SNPd
have been
genotyped for a sufficient number of SNPs. To identify samples with a
too-low call rate, use CheckGeno
. To calculate the call rate
for all samples, see the examples below.
Some parents indicated here as assignable may never be assigned by sequoia, for example parent-offspring pairs where it cannot be determined which is the older of the two, or grandparents that are indistinguishable from full avuncular (i.e. genetics inconclusive because the candidate has no parent assigned, and ageprior inconclusive).
The Pedigree
dataframe with 3 additional columns,
id.cat
, dam.cat
and sire.cat
, with coding similar to
that used by PedCompare
:
G |
Genotyped |
D |
Dummy or 'dummifiable' |
X |
Not genotyped and not dummifiable, or no parent in pedigree |
PedA <- getAssignCat(Ped_HSg5, rownames(SimGeno_example))
tail(PedA)
table(PedA$dam.cat, PedA$sire.cat, useNA="ifany")
# calculate call rate
## Not run:
CallRates <- apply(MyGenotypes, MARGIN=1,
FUN = function(x) sum(x!=-9)) / ncol(MyGenotypes)
hist(CallRates, breaks=50, col="grey")
GoodSamples <- rownames(MyGenotypes)[ CallRates > 0.8]
# threshold depends on total number of SNPs, genotyping errors, proportion
# of candidate parents that are SNPd (sibship clustering is more prone to
# false positives).
PedA <- getAssignCat(MyOldPedigree, rownames(GoodSamples))
## End(Not run)
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