Epicopy: Run Epicopy.
In sean-cho/Epicopy: Get CNV information from 450K array

Description Usage Arguments Details Value See Also Examples

Parses the CNA result from LRRtoCNA and writes a segment file and marker file for input into GISTIC 2.0.

epicopy(target_dir, output_dir = NULL, project_name = NULL,
  Normals = NULL, sampNames = NULL, QN = FALSE, Ref = "mode",
  mode.bw = 0.1, mode.method = "naive", normal.cnv = NULL,
  mean.center = TRUE, filterProbes = FALSE, retainedProbes = NULL,
  ncores = 1L, seg.undo.splits = "sdundo", seg.undo.SD = 2,
  filterbycount = TRUE, min_probes = 50, verbose = TRUE, ...)

`target_dir`	Target directory with IDAT files and sample sheet.
`output_dir`	Output directory. Defaults to current directory. If FALSE, no GISTIC 2.0 files will be outputted, but can be manually obtained using the function `export_gistic`.
`project_name`	Will be used as prefixes for any output.
`Normals`	Character string identifying column in sample sheet to scan for normals. Defaults to NULL, using all included Epicopy normals. See details for information on the normals and additional arguments.
`sampNames`	Character string identifying column in sample sheet to use for sample names. If NULL, uses the default `read.metharray.exp` values, which are the ChipNo_Position.
`QN`	Logical. Quantile normalize post funnorm? Defaults to `FALSE`.
`Ref`	String. One of 'mode' or 'median'. How to calculate LRR.
`mode.bw`	If Ref = 'mode', uses this bw to estimate the mode. Defaults to 0.1.
`mode.method`	If Ref = 'mode', uses this method to estimate the mode. Defaults to 'naive'.
`normal.cnv`	Logical. Defaults to NULL which evaluates the Normal input. If Normal is user input normal tissues, then defaults to TRUE. Otherwise FALSE.
`mean.center`	Logical. Perform mean centering of final data.
`filterProbes`	Logical. Filter probe by TCGA defined 450K probes adjacent to a known SNP.
`retainedProbes`	Character. IF filterProbes is TRUE, denotes probes to keep. If NULL, uses probes retained by TCGA.
`ncores`	Integer. Number of cores to use for segmentation. Defaults to 1.
`seg.undo.splits`	Undo.splits argument for `segment` from `DNAcopy`. Default: `'sdundo'`.
`seg.undo.SD`	undo.SD argument for `segment`. Default: 2.
`filterbycount`	Logical. Recommended. Should the output segment file be filtered for having at least `min_probes` number of probes in the segment.
`min_probes`	Number of probes to filter against.
`verbose`	Logical. Verbose?
`...`	Passes argument to `getLRR`.

epicopy Master function to run epicopy from raw Illumina Methylation 450K data.

Epicopy reads the sample sheet provided by the user in the target_dir, imports the experiment, and returns a CNA file while writing gistic outputs at the output_dir.

If the user has their own normals, specify the column name in the samplesheet that contains the identifier 'normal' (not case sensitive). Else, they can specify one of 'all' (default, NULL), 'breast', 'lung', or 'thyroid' to use Epicopy included normals. The last alternative is NA which uses all the samples as references, under the assumption that the mode/median of all the samples are at 2n. The last is recommended either in samples with low CNV, or when there are many samples. See also getLRR.

Epicopy object and output files.

getLRR LRRtoCNA export_gistic RGChannelSet-class read.metharray.sheet read.metharray.exp

## Not run: 
# Run epicopy on included example TCGA data
input_loc <- system.file('extdata', 'raw_idat', package = 'Epicopy')
# No output directory, returns only local R object
epi_seg <- epicopy(input_loc, output_dir = FALSE) 

## End(Not run)