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
)

Arguments

group,

a character string. Two options: sudo or docker, depending to which group the user belongs

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

Value

a pdf, called cellCycleRange.pdf, with predicted cell cycle behaviour

Examples

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) }