makeOrderings: Construct orderings for count data given a model structure...
In baySeq: Empirical Bayesian analysis of patterns of differential expression in count data

Description Usage Arguments Details Value Author(s) References Examples

Given a model structure as defined in the ‘@groups’ slot of a countData object containing more than one group, it is often possible to define an ordering on the groups for a given genomic event. To take a simple example, if the average expression of a gene is higher in sample set A then in sample set B, then we might impose an ordering A>B.

1	makeOrderings(cD, orderingFunction)

`cD`	A `countData` object, or a descendant thereof.
`orderingFunction`	A function defining the orderings. If not given, will be taken from the ‘@densityFunction’ slot of ‘cD’. See Details, and examples below.

The orderingFunction takes 'dat' and 'observables' as arguments. 'dat' is equivalent to the ‘@data’ slot of the ‘cD’ object, and 'observables' the combined data in the ‘@sampleObservables’, ‘@rowObservables’ and ‘@cellObservables’ slots.

A countData with populated ‘@orderings’ slot.

Thomas J. Hardcastle

Hardcastle T.J., and Kelly, K. baySeq: Empirical Bayesian Methods For Identifying Differential Expression In Sequence Count Data. BMC Bioinformatics (2010)

# load test data
data(simData)

# Create a countData object from test data

replicates <- c("simA", "simA", "simA", "simA", "simA", "simB", "simB", "simB", "simB", "simB")
groups <- list(NDE = c(1,1,1,1,1,1,1,1,1,1), DE = c(1,1,1,1,1,2,2,2,2,2))
CD <- new("countData", data = simData, replicates = replicates, groups = groups)
libsizes(CD) <- getLibsizes(CD)

# order on expression normalised for library size (scaling factor) and gene length

CD <- makeOrderings(CD, orderingFunction = function(dat, observables) dat / observables$libsizes)

# orderings calculated for DE group
head(CD@orderings)

# load test (paired) data
data(pairData)  

# create a countData object from paired data
pairCD <- new("countData", data = list(pairData[,1:4], pairData[,5:8]),
                  replicates = c(1,1,2,2),
                  groups = list(NDE = c(1,1,1,1), DE = c(1,1,2,2)),
               densityFunction = bbDensity)
libsizes(pairCD) <- getLibsizes(pairCD)

# order on (log-)ratio of pairs, with fudge-factor on zeros.

pairCD <- makeOrderings(pairCD, orderingFunction = function(dat, observables) {
                                      data <- dat / observables$libsizes               
                                      adjmin <- min(data[data > 0]) / 10
                                      log(data[,,1] + adjmin) - log(data[,,2] + adjmin)
})

# orderings calculated for DE group
head(pairCD@orderings)