Nothing
library(TReNA)
library(RUnit)
#----------------------------------------------------------------------------------------------------
printf <- function(...) print(noquote(sprintf(...)))
#----------------------------------------------------------------------------------------------------
runTests <- function()
{
test_BayesSpikeSolverConstructor()
test_ampAD.mef2c.154tfs.278samples.bayesSpike()
} # runTests
#----------------------------------------------------------------------------------------------------
test_BayesSpikeSolverConstructor <- function()
{
printf("--- test_BayesSpikeSolverConstructor")
#solver <- BayesSpikeSolver()
solver <- TReNA(matrix(), solver = "bayesSpike")
checkEquals(getSolverName(solver), "BayesSpikeSolver")
#checkTrue(all(c("BayesSpikeSolver", "Solver") %in% is(solver)))
} # test_BayesSpikeSolverConstructor
#----------------------------------------------------------------------------------------------------
test_ampAD.mef2c.154tfs.278samples.bayesSpike <- function()
{
printf("--- test_ampAD.mef2c.154tfs.278samples.bayesSpike")
load(system.file(package="TReNA", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))
target.gene <- "MEF2C"
mtx.asinh <- asinh(mtx.sub)
#print(fivenum(mtx.asinh) # [1] 0.000000 1.327453 3.208193 4.460219 7.628290)
trena <- TReNA(mtx.assay=mtx.asinh, solver="bayesSpike", quiet=FALSE)
tfs <- setdiff(rownames(mtx.asinh), "MEF2C")
tbl <- solve(trena, target.gene, tfs)
tbl.trimmed <- subset(tbl, abs(beta) > 0.1 & pval < 0.01)
# I don't think we need these anymore
#betas <- tbl.trimmed$beta
#big.abs.betas <- betas[abs(betas) > 1]
#checkTrue(length(big.abs.betas) > 20)
# Check number of results and correlation of results
checkTrue(nrow(tbl.trimmed) > 6)
checkTrue(cor(tbl.trimmed$beta, tbl.trimmed$gene.cor) > 0.6)
} # test_ampAD.mef2c.154tfs.278samples.bayesSpike
#----------------------------------------------------------------------------------------------------
if(!interactive()) runTests()
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