The genotypes probabilities can be calculated considering a global error (default method) or considering a genotype error probability for each genotype. Furthermore, user can provide directly the genotype probability matrix.
create_probs(
input.obj = NULL,
global_error = NULL,
genotypes_errors = NULL,
genotypes_probs = NULL
)
An object of class onemap
, i.e., a list with the following
components:
a matrix with integers indicating the genotypes read for each marker. Each column contains data for a marker and each row represents an individual.
number of individuals.
number of markers.
a vector with the
segregation type of each marker, as strings
.
a
vector with the segregation type of each marker, represented in a
simplified manner as integers, i.e. 1 corresponds to markers of type
"A"
; 2 corresponds to markers of type "B1.5"
; 3 corresponds
to markers of type "B2.6"
; 4 corresponds to markers of type
"B3.7"
; 5 corresponds to markers of type "C.8"
; 6 corresponds
to markers of type "D1"
and 7 corresponds to markers of type
"D2"
. Markers for F2 intercrosses are coded as 1; all other crosses
are left as NA
.
the name of the input file.
number of phenotypes.
a matrix with phenotypic values. Each column contains data for a trait and each row represents an individual.
matrix containing HMM emission probabilities
object of class onemap or onemap sequence
a integer specifying the global error value
a matrix with dimensions (number of individuals) x (number of markers) with genotypes errors values
a matrix with dimensions (number of individuals)*(number of markers) x possible genotypes (i.e., a ab ba b) with four columns for f2 and outcrossing populations, and two for backcross and RILs).
Cristiane Taniguti chtaniguti@tamu.edu
The genotype probability matrix has number of individuals x number of markers rows and four columns (or two if considering backcross or RILs populations), one for each possible genotype of the population. This format follows the one proposed by MAPpoly.
The genotype probabilities come from SNP calling methods. If you do not have them, you can use a global error or a error value for each genotype. The OneMap until 2.1 version have only the global error option.
Broman, K. W., Wu, H., Churchill, G., Sen, S., Yandell, B. (2008) qtl: Tools for analyzing QTL experiments R package version 1.09-43
make_seq
data(onemap_example_out)
new.data <- create_probs(onemap_example_out, global_error = 10^-5)
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