ccr.PlainTsvFile | R Documentation |
This function takes in input a sgRNA counts' object, as outputted (for example) by the
ccr.NormfoldChanges
function
and saves it as plaing tab delimited text file (which can be processed by MAGeCK [1]).
ccr.PlainTsvFile(sgRNA_count_object,
fprefix = "",
path = "./")
sgRNA_count_object |
sgRNA counts data object. |
fprefix |
A string specifying a name prefix of the tsv file which will contain the inputted sgRNA counts data object. |
path |
A string specifying the location where the tsv file will be saved. |
A string specifying the complete path of the saves tsv file.
Francesco Iorio (francesco.iorio@fht.org)
[1] Li, W., Xu, H., Xiao, T., Cong, L., Love, M. I., Zhang, F., et al. (2014). MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome Biology, 15(12), 554. [2] Hart, T., & Moffat, J. (2016). BAGEL: a computational framework for identifying essential genes from pooled library screens. BMC Bioinformatics, 17(1), 164.
ccr.NormfoldChanges
## Not run:
## Loading sgRNA library annotation file
data(KY_Library_v1.0)
## Deriving the path of the file with the example dataset,
## from the mutagenesis of the EPLC-272H colorectal cancer cell line
fn<-paste(system.file('extdata', package = 'CRISPRcleanR'),
'/EPLC-272H_counts.tsv',sep='')
## Loading, median-normalizing and computing fold-changes for the example dataset
normANDfcs<-ccr.NormfoldChanges(fn,min_reads=30,
EXPname='EPLC-272H',
libraryAnnotation = KY_Library_v1.0,
display=FALSE)
## saving median-normalised sgRNA counts' as a plain tsv file in ./EPLC-272H_sgRNA_count.tsv
uncorrected_fn<-ccr.PlainTsvFile(sgRNA_count_object = normANDfcs$norm_counts,fprefix = 'EPLC-272H')
uncorrected_fn
## End(Not run)
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