Description Usage Arguments Details Value Examples
The main function used to call and run the GCS-score algorithm.
1 2 3 |
celFile1 |
If a one comparison run is desired, enter the filename and path to the 1st Affymetrix CEL file |
celFile2 |
If a one comparison run is desired, enter the filename and path to the 2nd Affymetrix CEL file |
celTable |
If a batch run is desired, enter the filename and path to the CSV file containing the batch information |
celTab.names |
If set to |
typeFilter |
If set to |
method |
This determines the method used to group and tally the probes_ids when calculating GCS-scores. For Whole Transcriptome (WT) arrays, for gene-level (transcript_cluster_id-based) analysis, set |
rm.outmask |
If set to |
SF1 |
Input a pre-determined Scaling Factor (SF) for the 1st CEL file |
SF2 |
Input a pre-determined Scaling Factor (SF) for the 2nd CEL file |
fileout |
Determines if the resulting GCS-score coutput is written to disk in a CSV format following the completion of the function. By default, this is set to FALSE so unnecessary GCS-score outputs are not saved to disk after each run |
gzip |
If set to |
verbose |
If set to |
The input accepts individual CEL files or reads in a CSV file for batch runs. The user also inputs parameters to determine the method
used by the GCS-score algorithm to group and tally the individual probes on a given array.
A data.table
object with GCS-score values for the probe groupings (determined by the method
argument) and the relevant annotation informtaion
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | if (length(list.files(path = ".", pattern = "*.CEL")) != 0){
##Single run example:
# get the path to example CEL files in the package directory:
celpath1 <- system.file("extdata/ex_dat",
"MN_2_3.CEL", package = "GCSscore")
celpath2 <- system.file("extdata/ex_dat",
"MN_4_1.CEL", package = "GCSscore")
# run GCSscore() function directly on two .CEL files:
Ss2_clarS <- GCSscore(celFile1 = celpath1, celFile2 = celpath2)
# display selected columns of GCSscore output:
Ss2_clarS[1:6,c(1,3,6,7,8,11)]
## Batch run example:
# get the path to example CSV file in the package directory:
celtab_path <- system.file("extdata/ex_dat",
"Ss2_BATCH_example.csv", package = "GCSscore")
# read in the .CSV file with fread():
celtab <- fread(celtab_path)
# view structure of 'celTable' input:
celtab
# For the following example, the .CEL files are not in the working
# directory. The path to the .CEL files must be added to allow
# the GCSscore() function to find them.
# add path to celFile names in batch input:
path <- system.file("extdata/ex_dat",
"", package = "GCSscore")
celtab$CelFile1 <- celtab[,paste(path,CelFile1,sep="")]
celtab$CelFile2 <- celtab[,paste(path,CelFile2,sep="")]
# run GCSscore() function with batch input:
Ss_clarS_batch <- GCSscore(celTable = celtab, celTab.names = TRUE)
# display selected columns of GCSscore batch output:
Ss_clarS_batch[1:6,c(1,3,11,12,13,14,15,16)]
}
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