recatPrediction.Rd
This function executes a ubuntu docker which associates a cell cycle state to each cell
recatPrediction(
group = c("sudo", "docker"),
scratch.folder,
file,
separator,
geneNameControl = 0,
window = 1,
seed = 111
)
a character string. Two options: sudo or docker, depending to which group the user belongs
a character string indicating the path of the scratch folder
a character string indicating the folder where input data are located and where output will be written and matrix name "/bin/users/matrix.csv"
separator used in count file, e.g. '\t', ','
0 if the matrix has gene name without ENSEMBL code. 1 if the gene names is formatted like this : ENSMUSG00000000001:Gnai3. If the gene names is only ensamble name you have to run SCannoByGtf before start using this script.
number cells collapsed in a single point of the lot. This make less noisy the output generated by the predictor, default 10.
important parameter for reproduce the same result with the same input
a pdf, called cellCycleRange.pdf, with predicted cell cycle behaviour
if (FALSE) {
#preparing the data for the analysis
system("wget http://130.192.119.59/public/buettner_G1G2MS_counts.txt.zip")
unzip("buettner_G1G2MS_counts.txt.zip")
#annotating the data set to obtain the gene names in the format ensemblID:symbol
scannobyGtf(group="docker", file=paste(getwd(),"buettner_G1G2MS_counts.txt",sep="/"),
gtf.name="Mus_musculus.GRCm38.94.gtf", biotype="protein_coding",
mt=TRUE, ribo.proteins=TRUE,umiXgene=3, riboStart.percentage=0,
riboEnd.percentage=100, mitoStart.percentage=0, mitoEnd.percentage=100, thresholdGenes=100)
#running cell cycle prediction
recatPrediction(group="docker",scratch.folder="/data/scratch",
file=paste(getwd(), "annotated_buettner_G1G2MS_counts.txt", sep="/"),
separator="\t", geneNameControl=1, window=10, seed=111)
}