allele_specific_stutter_model {simDNAmixtures}

Stutter model where the expected stutter rate depends on the allele and locus

Description

Stutter model where the expected stutter rate depends on the allele and locus

Usage

allele_specific_stutter_model(stutter_types, size_regression)

Arguments

stutter_types

List. See stutter_type.

size_regression

Function, see read_size_regression.

Details

When a pg_model is constructed (see gamma_model), a stutter model can optionally be applied. The allele specific stutter model is commonly used with a log normal model. The expected stutter ratio for a parent allele at a locus is obtained from a linear regression of observed stutter ratios against allele length. For some loci or alleles the linear model may not be satisfactory. To override the expected stutter rates for specific alleles, a list of exceptions can be used. See stutter_type for more detail.

Value

Object of class stutter_model to be used by e.g. log_normal_model.

See Also

global_stutter_model for a stutter model where the expected stutter ratio does not depend on the locus or parent allele.

Examples

# we will define an allele specific stutter model for back stutter only

# prepare stutter regression
filename_bs_regression <- system.file("extdata",
"GlobalFiler_Stutter_3500.txt",package = "simDNAmixtures")
bs_regression <- read_stutter_regression(filename_bs_regression)

# prepare exceptions, i.e. where does the regression not apply?
filename_bs_exceptions <- system.file("extdata",
"GlobalFiler_Stutter_Exceptions_3500.csv",package = "simDNAmixtures")
bs_exceptions <- read_stutter_exceptions(filename_bs_exceptions)

# prepare a stutter type
backstutter <- stutter_type(name = "BackStutter", delta = -1,
                            stutter_regression = bs_regression,
                            stutter_exceptions = bs_exceptions)

# assign stutter model
size_regression <- read_size_regression(system.file("extdata",
"GlobalFiler_SizeRegression.csv",package = "simDNAmixtures"))
bs_model <- allele_specific_stutter_model(list(backstutter), size_regression)
bs_model