pedtools (version 0.9.0)

marker_attach: Attach markers to pedigrees

Description

In many applications it is useful to attach markers to their associated ped object. In particular for bigger projects with many markers, this makes it easier to manipulate the dataset as a unit. The function setMarkers() replaces all existing markers with the supplied ones, while addMarkers() appends the supplied markers to any existing ones.

Usage

setMarkers(x, m = NULL, alleleMatrix = NULL, locusAttributes = NULL,
  missing = 0, sep = NULL, ...)
addMarkers(x, m = NULL, alleleMatrix = NULL, locusAttributes = NULL,
  missing = 0, sep = NULL, ...)

Arguments

x

A ped object

m

Either a single marker object or a list of marker objects

alleleMatrix

A matrix with pedsize(x) rows, containing the observed alleles for one or several markers. The matrix must have either 1 or 2 columns per marker. If the former, then a sep string must be a given, and will be used to split all entries.

locusAttributes

A list of lists, with attributes for each marker. See Details for possible attributes.

missing

A single character (or coercible to one) indicating the symbol for missing alleles.

sep

If this is a single string, each entry of alleleMatrix is interpreted as a genotype, and will be split by calling strsplit(..., split = sep, fixed = T). For example, if the entries are formatted as "A/B", put sep = "/". Default: NULL.

...

Further arguments

Value

A ped object.

Details

The most general format of locusAttributes a list of lists, one for each marker, where possible entries in the inner lists are as follows (default values in parenthesis):

• alleles : a character vector with allele labels

• afreq : a numeric vector with allele frequencies (rep.int(1/L, L), where L = length(alleles))

• chrom : chromosome number (NA)

• posMb : physical location in megabases (NA)

• posCm : position in centiMorgan (NA)

• name : marker name (NA)

• mutmod : mutation model, or model name (NULL)

• rate : mutation model parameter (NULL)

If locusAttributes is just a single list of attributes (not a list of lists), then it is repeated to match the number of markers.

Two alternative format of locusAttributes are allowed: If a data.frame or matrix is given, an attempt is made to interpret it as a frequency database in allelic ladder format. Such an interpretation is also attempted if locusAttributes is a list of named frequency vectors (where the names are the allele labels).

Examples

# NOT RUN {
x = singleton(1)
m1 = marker(x, '1' = 1:2)
m2 = marker(x, '1' = 'a')

x = setMarkers(x, m1)
x = addMarkers(x, m2)
x

# Reversing the order of the markers
x = setMarkers(x, list(m2, m1))
x

# }