run_conumee | R Documentation |
Generate segment & log2r intensity files calculated by CONUMEE.
read intesity from file or object
run_conumee( intensities, anno_file = NULL, ctrl_file = "WB", Sample_Name = NULL, seg.folder = "Segments", log2r.folder = "log2r", arraytype = "450K", conumee.folder = "analysis/CONUMEE/", probeid = "probeid" ) read_intensity(infile, Sample_Name = NULL, probeid = "probeid")
intensities |
dataset with intensities. either dataframe or path to file. For big datasets '.fst' file is recomended. |
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 |
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" |
arraytype |
Methylation array type |
conumee.folder |
Parent working directory where you want to have your results. |
probeid |
name of column with probe ids. |
infile |
input path to file or object |
Log2r intensities and segment files.
#data("anno") #data("controls") #library(conumee) library(SummarizedExperiment) intensity<-readRDS("./analysis/ChAMP/intensities.rds") intensity<-conumee::CNV.load(intensity)@intensity run_conumee(intensities=intensity)
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