run.absCNSeq: main function to run absCNseq
In lixiangchun/lxctk: Li Xiangchun's tool-kit (lxctk)

Description Usage Arguments Details Value Author(s) Examples

This wrapper function accepts data files and user specified parameters and runs the absCNseq algorithm (modify input interface from absCNseq V1.0).

run.absCNSeq(seg.data, snv.data = NULL, res.dir, smp.name, seq.type = c("WES", "WGS"), alpha.min = 0.2, alpha.max = 1, tau.min = 1.5, tau.max = 5, min.freq = 0, min.seg.len = 0, qmax = 7, lamda = 0.5, verbose = FALSE)

`seg.data`	A data frame of 5 cols with colnames being `chrom`,`loc.start`,`loc.end`,`eff.seg.len`,`normalized.ratio`.
`snv.data`	A data frame of 3 cols with colnames being `chrom`,`position`,`tumor_var_freq`.
`res.dir`	The output directory
`smp.name`	Sample name
`seq.type`	Either "WES" (whole exome sequencing) or "WGS" (whole genome sequencing)
`alpha.min`	The minimum allowed value for tumor purity. Default is 0.20. If you do have the pathologist estimate, set it as the lower bound of the pathologist estimate is usually preferred.
`alpha.max`	The maximum allowed value for tumor purity. Default is 1.0. If you do have the pathologist estimate, set it as the upper bound of the pathologist estimate is usually preferred.
`tau.min`	The minimum allowed value for tumor ploidy
`tau.max`	The maximum allowed value for tumor ploidy
`min.sol.freq`	A solution should appear at least this many times to be kept. Singleton solutions are usually not trustable. By default (min.sol.freq=0), the program will only retain solutions that cover at least 1 percent of the search space.
`min.seg.len`	The minimum length of a segment to be included in computation. The default value is 200 bp for WES and 3000 bp for WGS.
`qmax`	Maximum allowed absolute copy number for any segments.
`lamda`	The relative weight of the segment copy ratio data over the SNV data. Must be a value in(0.0,1.0].
`verbose`

Please refer to the "example" folder to see the format of the input segmentation file or SNV file.

a list is returned

`searchRes`	a data frame giving the solution set (purity and ploidy pairs) ranked by their fitting errors
`absCN`	a data frame giving the absolute copy number estimates of tumor cells for the top first solution (purity and ploidy pair)
`absSNV`	a data frame giving the absolute multiplicity estimates of SNVs for the top first solution (purity and ploidy pair)
`orig.seg.dat`	original copy ratio data read from the input segmentation file
`seg.dat`	filtered copy ratio data
`orig.snv.dat`	original SNV data read from the input SNV file
`snv.dat`	filtered SNV data

Lei Bao

data("absCNseq", package="lxctk")
my.res.list <- run.absCNSeq(cn, snv, "myResult", "Sample1", seq.type="WES", min.seg.len=200)
seg.CN <- compute.absCN(my.res.list$seg.dat, my.res.list$searchRes[i,"alpha"], my.res.list$searchRes[i,"tau"])  # the i-th solution
plot.absCN(seg.CN, chromnum=1)  # plot chromosome 1