gc_correct: Perform a GC bias correction on nipt sample

In NIPTeR: Fast and Accurate Trisomy Prediction in Non-Invasive Prenatal Testing

Description

LOESS based GC bias correction algorithm described by Chen et al (2011)

Usage

gc_correct(nipt_object, method = "LOESS", include_XY = F, span = 0.75,
  ref_genome = "hg37")

Arguments

nipt_object	The object that will be corrected. This can either be a 'NIPTSample' or a 'NIPTControlGroup' object
method	To select the LOESS based method use "LOESS", to select the bin weights based method use "bin".
include_XY	Also apply correction to X and Y chromosomes?
span	The span for the LOESS fit. Only applicable when LOESS method is used.
ref_genome	The reference genome used. Either "hg37" or "hg38" default = "hg37"

Details

GC content bias is the correlation between the number of reads mapped to a specific genomic region and the GC content of this region. In NIPTeR, two GC bias correction algorithms have been implemented, the LOESS based method introduced by Chen et al. (2011) and the bin weight based method described by Fan and Quake (2010).

Value

Depending on the input object either a NIPTSample or a NIPTControlGroup object

Examples

## Not run: 
##Correct NIPTSample object using LOESS method
loess_corrected_sample <- gc_correct(nipt_object = sample_of_interest, method = "LOESS",
                                     include_XY = F, span = 0.75)
##Correct NIPTControlGroup object using bin method
gc_bin_corrected_control_group <- gc_correct(nipt_object = control_group, method = "bin", 
                                             include_XY = T)

## End(Not run)

NIPTeR documentation built on May 2, 2019, 7:55 a.m.