scannobyGtf | R Documentation |
This function executes the docker container annotate.1, where refGenome is used to annotate a single cell counts table with ensembl gene ids on first column using ENSEMBL GTF annotation
scannobyGtf(
group = c("docker", "sudo"),
file,
gtf.name,
biotype = NULL,
mt = c(TRUE, FALSE),
ribo.proteins = c(TRUE, FALSE),
umiXgene = 3,
riboStart.percentage = 20,
riboEnd.percentage = 70,
mitoStart.percentage = 1,
mitoEnd.percentage = 100,
thresholdGenes = 250
)
group |
a character string. Two options: |
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". The system recognize automatically csv as comma separated files and txt as tab separated file |
gtf.name |
a character string indicating the ENSEMBL gtf file |
biotype |
a character string the biotypes of interest |
mt |
a boolean to define if mitocondrial genes have to be removed, FALSE mean that mt genes are removed |
ribo.proteins |
a boolean to define if ribosomal proteins have to be removed, FALSE mean that ribosomal proteins (gene names starting with rpl or rps) are removed |
umiXgene |
a integer defining how many UMI are required to call a gene as present. default: 3 |
riboStart.percentage |
start range for ribosomal percentage, cells within the range are kept |
riboEnd.percentage |
end range for ribosomal percentagem cells within the range are kept |
mitoStart.percentage |
start range for mitochondrial percentage, cells within the range are retained |
mitoEnd.percentage |
end range for mitochondrial percentage, cells within the range are retained |
thresholdGenes |
parameter to filter cells according to the number og significative genes expressed |
one file: annotated_counts table, where ensembl ids are linked to gene symbols and a PDF showing the effect of ribo and mito genes removal. Filtered_annotated annotated counts table with only cells and genes given by filtering thresholds. A pdf showing the effect of genes counts of the filtering and a filteredStatistics.txt indicating how many cell and genes were filtered out
Raffaele Calogero, Luca Alessandri
## Not run:
system("wget http://130.192.119.59/public/testSCumi_mm10.csv.zip")
library(rCASC)
system("unzip testSCumi_mm10.csv.zip")
#filtering low quality cells
lorenzFilter(group="docker",scratch.folder="/data/scratch/",
file=paste(getwd(),"testSCumi_mm10.csv",sep="/"),
p_value=0.05,separator=',')
#running annotation and removal of mit and ribo proteins genes
#download mouse GTF for mm10
system("wget ftp://ftp.ensembl.org/pub/release-92/gtf/mus_musculus/Mus_musculus.GRCm38.92.gtf.gz")
system("gunzip Mus_musculus.GRCm38.92.gtf.gz")
scannobyGtf(group="docker", file=paste(getwd(),"testSCumi_mm10.csv",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)
## End(Not run)
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