wolfpsort: predict subcellular protein localization with WoLFpsort
In gogleva/SecretSanta: flexible pipelines for secretome prediction

Description Usage Arguments Value Examples

This function runs WoLF PSORT to predict protein cellular sub-localisation and returns the most probbale one. Including this step in secretome prediction pipelines provides additional supportig evidence that a protein might be secreted and deposited outside the cell.

Recommended to run on the late stages of secretome prediction pipeline.

Also see targetp function - for similar functionality.

1 2	wolfpsort(input_obj, organism = c("plant", "animal", "fungi"), run_mode = c("starter", "piper"), paths = NULL)

`input_obj`	Object of CSBResult class
`organism`	set relevant taxonomic group, options include: plant, animal, fungi;
`run_mode`	starter - if it is the first step in pipeline; piper - if you run this function on the output of other methods;
`paths`	if wolfpsort is not acessible globally, a file conatining a full path to it's executable should be provided; for details please check SecretSanta vignette.

object of WolfResult class

# read fasta file in AAStringSet object
aa <- readAAStringSet(system.file("extdata","sample_prot_100.fasta",
package = "SecretSanta"))
# assign this object to the input_fasta slot of CBSResult object
inp <- CBSResult(in_fasta = aa[1:10])
# run signalp2 on the initial file:
step1_sp2 <- signalp(inp, version = 2, organism ='euk',
run_mode = "starter", legacy_method = 'hmm')
# run wolfpsort on the signalp output:
w <- wolfpsort(step1_sp2, 'fungi', run_mode = 'piper')