computeCoverage: Compute effort-coverage values
In Genominator: Analyze, manage and store genomic data

Description Usage Arguments Details Value Author(s) See Also Examples

Compute fraction coverage obtained for a certain degree of sequencing effort.

computeCoverage(expData, annoData,
  cutoff = function(x, anno, group) { x > 10 },
  effort = seq(1e+05, 5e+07, length = 20),
  smooth = function(probs) { probs },
  groups = rep("ALL", length(what)),
  what = getColnames(expData, all = FALSE),
  totals = summarizeExpData(expData, what = what, verbose = verbose),
  ignoreStrand = FALSE, verbose = getOption("verbose"), ...)

`expData`	An `ExpData` object.
`annoData`	A data frame which must contain the columns `chr`, `start`, `end` and `strand` which specifies annotation regions of interest.
`cutoff`	A predicate which determines when a region of annotation has been "sequenced". This function takes three arguments x = number of reads in region, anno = the annotation description of the region, group = the group it is in.
`effort`	Effort is a vector of how much sequencing has been done.
`smooth`	A function which takes as input the vector of probabilities and must return the probabilities.
`groups`	The different groups for which to calculate coverage.
`what`	The different columns, must be the same length as the groups.
`totals`	The lane totals, or some other totals. This allows us to estimate the sampling probability vector.
`ignoreStrand`	Whether or not to add over strands.
`verbose`	Do you want to see output.
`...`	Extra argument passed to cutoff.

This argument is pretty general as different ways of specifying the arguments allows one to compute "coverage" under a lot of different definitions.

Returns an object of class genominator.coverage. Pretty much you'll want to call plot on this object.

James Bullard bullard@berkeley.edu, Kasper Daniel Hansen khansen@jhsph.edu

See the plot.genominator.coverage for the plotting method and the Genominator vignette for details.

ed <- ExpData(system.file(package = "Genominator", "sample.db"),
              tablename = "raw")
data("yeastAnno")
a <- computeCoverage(ed, yeastAnno, effort = 2^(5:18),
                     cutoff = function(x, ...) x > 1, smooth = FALSE)
names(a)