strvalidator (version 0.1)

calculateBalance: Calculate balance

Description

calculateBalance calculates the inter and intra locus balance.

Usage

calculateBalance(data, perSample = TRUE, lb = "prop",
    perDye = TRUE, minHeight = NULL, maxHeight = NULL)

Arguments

data

a data frame containing at least 'Sample.Name', 'Marker', 'Height', Dye', and 'Zygosity'.

perSample

logical, default TRUE calculates balance for each sample, FALSE calculates the avrage across all samples.

lb

string. 'prop' is defualt and locus balance is calculated proportionally in relation to the whole sample. 'norm' locus balance is normalised in relation to the locus with the highest total peakheight.

perDye

logical, default is TRUE and locus balance is calculated within each dye. FALSE locus balance is calculated globally.

minHeight

integer giving the lower bound.

maxHeight

integer giving the upper bound.

Value

• data.frame with with columns 'Sample.Name', 'Marker', 'Hb', 'Lb', 'MpH'. Or 'Sample.Name','Marker','Hb.n', 'Hb.Mean', 'Hb.Sd', 'Hb.95','Lb.n', 'Lb.Mean', 'Lb.Sd'.

Details

Takes (GM-formatted) data for samples as input (Must be filtered to contain the clean profile??) Seem to give the same result filtered/not filtered). NB! Remove ladder

Examples

data(ref1)
data(set1)
# Format data frame.
ref1 <- slim(data=ref1, fix=c("Sample.Name","Marker"), stack=c("Allele"))

# Indicate heterozygous / homozygous alleles.
ref1 <- calculateZygosity(ref1)

# Remove all except positive control samples.
set1 <- trim(data=set1, samples="PC")

# Format data frame.
set1 <- slim(data=set1, fix=c("Sample.Name","Marker"), stack=c("Allele","Height"))

# Filter out data matching alleles in reference.
set1 <- filterProfile(data=set1, ref=ref1)

# Add zygosity.
set1$Zygosity <- rep(ref1$Zygosity,8)

# Add dye.
set1 <- addDye(data=set1, kit="ESX17")

# Calculate average balances.
calculateBalance(data=set1, perSample=FALSE)