seuratPCAEval.Rd
This function estimates the information content of the PCs of the experiment, required by Seurat clustering .
seuratPCAEval( group = c("sudo", "docker"), scratch.folder, file, separator, logTen = 0, seed = 1111, sparse = FALSE, format = "NULL" )
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 path of the file, with file name and extension included |
separator, | separator used in count file, e.g. '\t', ',' |
logTen, | 1 if the count matrix is already in log10, 0 otherwise |
seed, | important value to reproduce the same results with same input |
sparse, | boolean for sparse matrix. A sparse matrix is a format that reduces the size of the matrix, considering only positions different from 0. The format supported in rCASC is the one generated by 10XGenomics output: genes.tsv, barcodes.tsv and matrix.tbx. |
format, | output file format csv or txt. Only required if sparse matrix is used |
Plot with PCA scores is provided to detect the PCA dimensions to be used in Seurat clustering algorithm
Luca Alessandri, alessandri [dot] luca1991 [at] gmail [dot] com, University of Torino
if (FALSE) { system("wget http://130.192.119.59/public/section4.1_examples.zip") unzip("section4.1_examples.zip") setwd("section4.1_examples") system("wget ftp://ftp.ensembl.org/pub/release-94/gtf/homo_sapiens/Homo_sapiens.GRCh38.94.gtf.gz") system("gzip -d Homo_sapiens.GRCh38.94.gtf.gz") system("mv Homo_sapiens.GRCh38.94.gtf genome.gtf") scannobyGtf(group="docker", file=paste(getwd(),"bmsnkn_5x100cells.txt",sep="/"), gtf.name="genome.gtf", biotype="protein_coding", mt=TRUE, ribo.proteins=TRUE,umiXgene=3) seuratPCAEval(group="docker",scratch.folder="/data/scratch/", file=paste(getwd(), "annotated_bmsnkn_5x100cells.txt", sep="/"), separator="\t", logTen = 0, seed = 111, format="NULL") }