setFixedParameter: Set fixed allele read biases and mismapping rate

In tomoyukif/GBScleanR: Error correction tool for noisy genotyping by sequencing (GBS) data

Set fixed allele read biases and mismapping rate

Description

Set fixed allele read biases and mismapping rates of markers

Usage

setFixedParameter(object, bias = NULL, mismap = NULL, parent_geno = FALSE, ...)

## S4 method for signature 'GbsrGenotypeData'
setFixedParameter(object, bias, mismap, parent_geno)

Arguments

object	A GbsrGenotypeData object.
bias	A numeric vector of fixed allele read biases to be assigned to valid markers. The length of bias vector should match the number of valid markers.
mismap	A numeric matrix of fixed reference and alternative read mismapping rates to be assigned to valid markers. The number of rows of the given matrix should match the number of valid markers and should have two columns that are for reference and alternative read mismapping rates, respectively.
parent_geno	A logical value indicating whether to use fixed parental genotypes in the genoype estimation by estGeno(). This mode requires the estimated genotypes for parental samples that were estimated by estGeno() and stored in the GDS file linked to the input GbsrGenotypeData object.
...	Unused.

Details

If you have already executed genotype estimation and want to reuse the marker-wise allele read biases and mismapping rates estimated in the completed run of estGeno(), you can use them in the next genotype estimation run. For example, if you want to estimate genotypes with different argument settings of setGeno(), it is worth to set fixed parameters and run estGeno() with setting optim = FALSE to skip time-consuming iterative parameter optimization steps but use the estimated parameters from the first run to incorporate the marker-wise error parameters. Since the bias set by setFixedParameter() function is the reference allele read bias, the values 0 and 1 mean that the marker only gives alternative and reference allele reads, respectively. The values in the bias vector are assigned to the valid markers. Similarly, the values in the mismap matrix are assigned to the valid markers in the order they appear in the rows.

Value

A GbsrGenotypeData object after adding dominant marker information

Examples

# Create a GDS file from a sample VCF file.
vcf_fn <- system.file("extdata", "sample.vcf", package = "GBScleanR")
gds_fn <- tempfile("sample", fileext = ".gds")
gbsrVCF2GDS(vcf_fn = vcf_fn, out_fn = gds_fn, force = TRUE)

# Load data in the GDS file and instantiate a [GbsrGenotypeData] object.
gds <- loadGDS(gds_fn)

# Not run.
# Run estGeno() and reuse the estimated parameters in the second run.
# gds <- makeScheme(gds, generation = 2, crosstype = "self")
# gds <- estGeno(gds)
# fixed_param <- getFixedParameter(gds)
# gds <- setFixedParameter(gds,
#                          bias = fixed_param$bias,
#                          mismap = fixed_param$mismap)
# gds <- estGeno(gds, optim = FALSE, call_threshold = 0.5)

# You can also set arbitrary values.
bias <- sample(seq(0, 1, 0.01), nmar(gds), replace = TRUE)
mismap <- cbind(sample(seq(0, 0.2, 0.01), nmar(gds), replace = TRUE),
                sample(seq(0, 0.2, 0.01), nmar(gds), replace = TRUE))
gds <- setFixedParameter(gds, bias = bias, mismap = mismap)

# Close the connection to the GDS file
closeGDS(gds)

tomoyukif/GBScleanR documentation built on June 1, 2025, 10:13 p.m.