run_cnv.methyl: Generate segment & log2r intensity files calculated by...

In ijcBIT/cnv.methyl: cnv.methyl finds copy number alteration from methylation idat files

Generate segment & log2r intensity files calculated by CONUMEE.

Description

Generate segment & log2r intensity files calculated by CONUMEE.

Usage

run_cnv.methyl(
  targets,
  ref_genes = "all",
  cn_genes = NULL,
  Kc_method,
  out = "analysis/intermediate/",
  RGset = T,
  purity = NULL,
  arraytype = "450K",
  folder = NULL,
  anno_file = NULL,
  ctrl_file = "WB",
  Sample_Name = NULL,
  ncores = NULL,
  seg.folder = "Segments",
  log2r.folder = "log2r",
  conumee.folder = "analysis/CONUMEE/",
  probeid = "probeid",
  intensities = NULL
)

Arguments

targets	A sample sheet with the required fields for minfi to load files.
ref_genes	Granges object with subset of genes to use for cnv analysis.
cn_genes	Used to subset genes from the reference set. Needed in order to generate new Kc from a reference set, where cn_genes are previously known genes to be altered in a given cn_state. Otherwise use ref_genes.
Kc_method	Choose which Kc you want to use. Either "curated" or "balanced. The first comes from a list of 94 genes manually selected by experts and an uneven proportion of cancers. The second one comes from all genes and balanced proportion of cancer types. default= balanced
out	Parent working directory where you want to have your results.
RGset	Whether you want normalised "RGChannelSet" or "RGChannelSetExtended" to be saved or not. path=out
purity	Whether or not you want purity imputed by Rfpurify. Default=TRUE.
arraytype	Methylation array type
folder	this directory will be created as the combination of out and subf. if you save the csv file inside this folder it will be used by minfi::read.450k.sheet.
anno_file	anno file CNV.anno object saved as .rds. default CNV_Germline_GSITIC2_BROAD_SNP6.merged.151117.hg19.CNV.txt
ctrl_file	CNV data object with intensities from the controls group. must be compressed as '.rds' file format, default uses 96 WB samples. Default='WB'
Sample_Name	Samples to be analysed. If is NULL all columns in input file will be used. Accepts numbered index and names. Default=NULL
ncores	number of cores to use.
seg.folder	Subfolder inside results where segment files are saved. The segments are generated with CONUMEE CNV.segment(CNV.detail(CNV.bin(fit))) default = "Segments"
log2r.folder	Subfolder inside results where log2r values are saved. log2r values are the log2 ratio of the intensities(_GRN + _RED channel) between the query and the reference set (control) as returned by CNV.fit function from CONUMEE. default = "log2r"
conumee.folder	Parent working directory where you want to have your results.
probeid	name of column with probe ids.
intensities	dataset with intensities. either dataframe or path to file. For big datasets '.fst' file is recomended.

Value

data.frame with metadata from segmentation, genomic ranges, genes and scna for each of the genes

Examples

#data("TrainingSet_Sample_sheet")
#ss<-TrainingSet_Sample_sheet[1:56,]
t0<-Sys.time()
cnv<-cnv.methyl(targets=ss)
t1<-Sys.time()
cnv
print(paste0("elapsed time: ",t1-t0))

ijcBIT/cnv.methyl documentation built on Jan. 10, 2023, 7:51 a.m.