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 )
group, | a character string. Two options: sudo or docker, depending to which group the user belongs |
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scratch.folder, | a character string indicating the path of the scratch folder |
file, | 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, | separator used in count file, e.g. '\t', ',' |
geneNameControl, | 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. |
window, | number cells collapsed in a single point of the lot. This make less noisy the output generated by the predictor, default 10. |
seed, | important parameter for reproduce the same result with the same input |
a pdf, called cellCycleRange.pdf, with predicted cell cycle behaviour
Luca Alessandri , alessandri [dot] luca1991 [at] gmail [dot] com, University of Torino
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) }