computeCoverage {Genominator} | R Documentation |
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 |
annoData |
A data frame which must contain the columns |
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)