SPIAssay (version 1.0.0)

SPIATest: Function to compute SPIA test

Description

Function SPIATest computes SPIA distance and performs probabilistic test on a set of cell lines.

Usage

SPIATest(x, row.names = TRUE, test.prob = TRUE, test.param = list(Pmm = 0.1, nsigma = 2, Pmm_nonM = 0.6, nsigma_nonM = 3, PercValidCall=0.9),  verbose = FALSE)

Arguments

x

a matrix with a column for each cell line and a row for each SNP

row.names

specify if the first column of x contains SNPs names/identificators

test.prob

specify if the function has to perform SPIA probabilistic test

test.param

specify the parameters of the probabilistic test. - Pmm: SNP probability of mismatch in a matching population - nsigma: area limit for Pmm - Pmm_nonM: SNP probability of mismach in a non matching population - nsigma_nonM: area limit for Pmm_nonM - PercValidCall: percentage of valid SNP calls to consider the test valid

verbose

print verbose information

Value

SPIAresult

a matric with a line for each cell line and with columns with the informationss about distances In particular, each row of SPIAresult has 7 columns: 1. SPIA distance 2. number of valid calls 3. number of total calls 4. number of calls where one of the two SPNs are not available 5. number of calls where both SNPs are not available 6. number of calls where SNP change from AA, BB to AB or from AB to AA, BB 7. number of calls where SNP change from AA to BB or from BB to AA

parameters

the parameters used by the test (test.param)

input.param

the number of samples (N_samples), the number of SNPs (N_SNPs), and if the probabilistic test has been done (test.prob)

Examples

library(SPIAssay)

# An example of genotype calls with:
# - four cell lines
# - for each cell line five SNP calls
GenotypeCalls <- rbind(
c("SNP1", "AA", "AA", "AB", "AB"),
c("SNP2", "NoCall", "AA", "AB", "AB"),
c("SNP3", "AB", "AB", "AA" , "AB"),
c("SNP4", "BB", "BB", "BB", "BB"),
c("SNP5", "AB", "BB", "AA", "AA"))
colnames(GenotypeCalls) <- c("SNP_ID","CellLine1","CellLine2","CellLine3","CellLine4")

# Encode the data into SPIA format.
# SPIA uses 0 for AA, 1 for BB, 2 for AB, and NA for NoCall
# therefore, GenotypeCalls has to be encoded by meand of
# toSPIAData
encoding <- c("AA","BB","AB","NoCall")
SPIAGenotypeCalls <- toSPIAData(GenotypeCalls,encoding)

# Perform SPIA analysis
SPIAanalysis <- SPIATest(SPIAGenotypeCalls)
# This analysis give an error because there are not enough SNPs

# Perform SPIA analysis with parameters SPIAParam to reduce the 'similar' region
SPIAParam <- list(Pmm = 0.1, nsigma = 1, Pmm_nonM = 0.6, nsigma_nonM = 1, PercValidCall=0.7)
SPIAanalysis <- SPIATest(SPIAGenotypeCalls, row.names = TRUE, test.prob = TRUE, SPIAParam)