Compare, count and identify different types of relative pairs between two pedigrees, or within one pedigree.
ComparePairs(
Ped1 = NULL,
Ped2 = NULL,
Pairs2 = NULL,
GenBack = 1,
patmat = FALSE,
ExcludeDummies = TRUE,
DumPrefix = c("F0", "M0"),
Return = "Counts"
)Depending on Return, one of the following, or a list with all:
(the default), a matrix with counts, with the classification in
Ped1 on rows and that in Ped2 in columns. Counts for
'symmetrical' pairs ("FS", "HS", "MHS", "PHS", "FC1", "DFC1", "U","X") are
divided by two.
a matrix with one row per relationship type and four columns
, named as if Ped1 is the true pedigree:
total number of pairs with that relationship in Ped1,
and occurring in Ped2
Number of pairs with same relationship in Ped2 as in
Ped1
Number of pairs with 'higher' relationship in Ped2 as
in Ped1 (e.g. FS instead of HS; ranking is the order given
below)
Number of pairs with 'lower' relationship in Ped2 as in
Ped1, but not unrelated in Ped2
a 2xNxN array (if Ped2 or Pairs2 is specified)
or a NxN matrix , where N is the total number of individuals occurring in
Ped1 and/or Ped2.
a dataframe with \(N^2\) rows and four columns:
First individual of the pair
Second individual of the pair
the relationship category in Ped1, as a factor with all
considered categories as levels, including those with 0 count
the relationship category in Ped2
Each pair is listed twice, e.g. once as P and once as O, or twice as FS.
first (e.g. original/reference) pedigree, dataframe with 3 columns: id-dam-sire.
optional second (e.g. inferred) pedigree.
optional dataframe with as first three columns: ID1-ID2-
relationship, e.g. as returned by GetMaybeRel. Column names
and any additional columns are ignored. May be provided in addition to, or
instead of Ped2.
number of generations back to consider; 1 returns parent-offspring and sibling relationships, 2 also returns grandparental, avuncular and first cousins. GenBack >2 is not implemented.
logical, distinguish between paternal versus maternal relative pairs?
logical, exclude dummy IDs from output? Individuals
with e.g. the same dummy father will still be counted as paternal halfsibs.
No attempt is made to match dummies in one pedigree to individuals in the
other pedigree; for that use PedCompare.
character vector with the prefixes identifying dummy
individuals. Use 'F0' ('M0') to avoid matching to regular individuals with
IDs starting with 'F' ('M'), provided Ped2 has fewer than 999 dummy
females (males).
return a matrix with Counts or a Summary of the
number of identical relationships and mismatches per relationship, or
detailed results as a 2xNxN Array or as a Dataframe.
All returns a list with all four.
By default (GenBack=1, patmat=FALSE) the following 7 relationships are
distinguished:
S: Self (not included in Counts)
MP: Parent
O: Offspring (not included in Counts)
FS: Full sibling
HS: Half sibling
U: Unrelated, or otherwise related
X: Either or both individuals not occurring in both pedigrees
In the array and dataframe, 'MP' indicates that the second (column) individual is the parent of the first (row) individual, and 'O' indicates the reverse.
When GenBack=1, patmat=TRUE the categories are (S)-M-P-(O)-FS-MHS-PHS-
U-X.
When GenBack=2, patmat=TRUE, the following relationships are
distinguished:
S: Self (not included in Counts)
M: Mother
P: Father
O: Offspring (not included in Counts)
FS: Full sibling
MHS: Maternal half-sibling
PHS: Paternal half-sibling
MGM: Maternal grandmother
MGF: Maternal grandfather
PGM: Paternal grandmother
PGF: Paternal grandfather
GO: Grand-offspring (not included in Counts)
FA: Full avuncular; maternal or paternal aunt or uncle
HA: Half avuncular
FN: Full nephew/niece (not included in Counts)
HN: Half nephew/niece (not included in Counts)
FC1: Full first cousin
DFC1: Double full first cousin
U: Unrelated, or otherwise related
X: Either or both individuals not occurring in both pedigrees
Note that for avuncular and cousin relationships no distinction is made
between paternal versus maternal, as this may differ between the two
individuals and would generate a large number of sub-classes. When a pair is
related via multiple paths, the first-listed relationship is returned. To get
all the different paths between a pair, use GetRelM with
Return='Array'.
When GenBack=2, patmat=FALSE, MGM, MGF, PGM and PGF are combined
into GP, with the rest of the categories analogous to the above.
If Pairs2 is as returned by GetMaybeRel
(identified by the additional column names 'LLR' and 'OH'), these
relationship categories are appended with an '?' in the output, to
distinguish them from those derived from Ped2.
When Pairs2$TopRel contains values other than the ones listed among
the return values for the combination of patmat and GenBack,
they are prioritised in decreasing order of factor levels, or in decreasing
alphabetical order, and before the default (ped2 derived) levels.
The matrix returned by DyadCompare [Deprecated] is a subset
of the matrix returned here using default settings.
PedCompare for individual-based comparison;
GetRelM for a pairwise relationships matrix of a single
pedigree; PlotRelPairs for visualisation of relationships
within each pedigree.
To estimate P(actual relationship (Ped1) | inferred relationship (Ped2)),
see examples at EstConf.
PairsG <- ComparePairs(Ped_griffin, SeqOUT_griffin[["Pedigree"]],
patmat = TRUE, ExcludeDummies = TRUE, Return = "All")
PairsG$Counts
# pairwise correct assignment rate:
PairsG$Summary[,"OK"] / PairsG$Summary[,"n"]
# check specific pair:
PairsG$Array[, "i190_2010_M", "i168_2009_F"]
# or
RelDF <- PairsG$Dataframe # for brevity
RelDF[RelDF$id.A=="i190_2010_M" & RelDF$id.B=="i168_2009_F", ]
# Colony-style lists of full sib dyads & half sib dyads:
FullSibDyads <- with(RelDF, RelDF[Ped1 == "FS" & id.A < id.B, ])
HalfSibDyads <- with(RelDF, RelDF[Ped1 == "HS" & id.A < id.B, ])
# Use 'id.A < id.B' because each pair is listed 2x
Run the code above in your browser using DataLab