bi.edivisive.findCNVs: Find copy number variations (edivisive, bivariate)
In AneuFinder: Analysis of Copy Number Variation in Single-Cell-Sequencing Data

Classify the binned read counts into several states which represent copy-number-variation. The function uses the e.divisive function to segment the genome.

1 2	bi.edivisive.findCNVs(binned.data, ID = NULL, CNgrid.start = 0.5, R = 10, sig.lvl = 0.1)

`binned.data`	A GRanges-class object with binned read counts.
`ID`	An identifier that will be used to identify this sample in various downstream functions. Could be the file name of the `binned.data` for example.
`CNgrid.start`	Start parameter for the CNgrid variable. Very empiric. Set to 1.5 for normal data and 0.5 for Strand-seq data.
`R`	method-edivisive: The maximum number of random permutations to use in each iteration of the permutation test (see `e.divisive`). Increase this value to increase accuracy on the cost of speed.
`sig.lvl`	method-edivisive: The level at which to sequentially test if a proposed change point is statistically significant (see `e.divisive`). Increase this value to find more breakpoints.