read.interval {wgaim}R Documentation

Read in and estimate a linkage map and interval information

Description

Reads genotypic marker data in a wide range of formats and estimates the appropriate linkage map via Bromans read.cross function (see Details). Additionally, this function imputes missing markers and also estimates interval information appropriate for further analysis.

Usage

read.interval(format = c("csv", "csvr", "csvs", "csvsr", "mm",
"qtx", "tlcart", "gary", "karl"), dir = getwd(), file, genfile, mapfile,
phefile, chridfile, mnamesfile, pnamesfile, na.strings = c("-", "NA"),
genotypes = c("A", "B"), estimate.map = TRUE, convertXdata = TRUE,
missgeno = "MartinezCurnow", rem.mark = TRUE, id = "id",
subset = NULL, ...)

Arguments

format see read.cross
dir see read.cross
file see read.cross
genfile see read.cross
mapfile see read.cross
phefile see read.cross
chridfile see read.cross
mnamesfile see read.cross
pnamesfile see read.cross
na.strings see read.cross
genotypes see read.cross
estimate.map see read.cross
convertXdata see read.cross
missgeno a character string determining how missing values in the linkage map should be imputed. If "Broman", then missing values are imputed according to Bromans rules. If "MartinezCurnow" then missing values are imputed according to the rules of Martinez & Curnow (1994) (see reference list). The default is "MartinezCurnow"
rem.mark logical value. If TRUE redundant markers are deleted and placed in the component of the object (see details). Defaults to TRUE.
id the name of the unique identifier for each row of genotype data (see details). Defaults to "id"
subset A possible character vector naming the subset of chromosomes to be returned. Defaults to NULL implying return all chromosomes.
... Any other arguments to be passed to read.cross for the appropriate reading in of the data from a file (see read.cross for more details).

Details

This function uses a *modified* verison of Bromans' read.cross function to read in the genotypic data and estimate the linkage map. This *strict* modification only allows two genotypes which are the defaults "A" and "B". Attempting more than this will cause an error.

Bromans' read.cross and this function by default read genotypic information as well as phenotypic information if the data contains any. In general, this phenotypic component of the file *should* contain, at least, a column to identify each row of the data uniquely. The argument id is used for the purpose of identifying this column. An error will be induced otherwise.

The output of this function differs slightly from read.cross by the inclusion of additional components to the returned object. To ensure that functions of the qtl package could still be used with the returned object from this function the class structure from read.cross has been maintained. The returned object also inherits the class "interval" for forwards compatibility with functions available in the wgaim package.

Value

a list of class "cross" that also inherits the class "interval". The list contains the following components

geno This is a list with elements named by the corresponding names of the chromosomes. Each chromosome is itself a list with six elements: "data" is the actual estimated map matrix with rows as individuals named by "id" and markers as columns; "map" is a vector of marker positions on the corresponding chromosome; "argmax" is identical to "data" matrix but with all NA's replaced by imputed values according to the rules of "missgeno"; "dist" contains the genetic distance between adjacent markers or the genetic distances of the intervals; "theta" contains the recombination fractions for each interval; "intval" contains the recalculated intervals based on the recombination fractions and the missing marker information.
cor.markers If rem.mark = TRUE, a three column matrix with each row describing which pairwise markers are correlated and what chromosome they are from.
pheno A data.frame of phenotypic information with rows as individuals read in from read.cross. A copy of the column named by the "id" argument can be found here (see read.cross)

Author(s)

Julian Taylor, Simon Diffey, Ari Verblya and Brian Cullis

References

Martinez, O., Curnow. R. N. (1994) Missing markers when estimating quantitative trait loci using regression mapping. Heredity, 73, 198-206.

Verbyla, A. P., Cullis, B. R., Thompson, R (2007) The analysis of QTL by simultaneous use of the full linkage map. Theoretical And Applied Genetics, 116, 95-111.

See Also

read.cross

Examples


## Not run: 
# read in linkage map from a rotated .CSV file with "id" as the
# identifier for each unique row

racca <- read.interval("csvr", file="raccasgroups.csv", genotypes=c("A","B"),
missgeno="MartinezCurnow", id = "id", na.strings = c("-", "NA"))

# plot linkage map

link.map(racca, cex = 0.5)
## End(Not run)

[Package wgaim version 0.2 Index]