View source: R/ORFs_annotations.R
artificial.orfs | R Documentation |
Usefull to see if short ORFs prediction is dependent on length.
Split cds first in two, a start part and stop part.
Then say how large the two parts can be and merge them together.
It will sample a value in range give.
Parts will be forced to not overlap and can not extend outside
original cds
artificial.orfs(
cds,
start5 = 1,
end5 = 4,
start3 = -4,
end3 = 0,
bin.if.few = TRUE
)
cds |
a GRangesList of orfs, must have width %% 3 == 0 and length >= 6 |
start5 |
integer, default: 1 (start of orf) |
end5 |
integer, default: 4 (max 4 codons from start codon) |
start3 |
integer, default -4 (max 4 codons from stop codon) |
end3 |
integer, default: 0 (end of orf) |
bin.if.few |
logical, default TRUE, instead of per codon,
do per 2, 3, 4 codons if you have few samples compared to lengths wanted,
If you have 4 cds' and you want 7 different lengths, which is the standard,
it will give you possible nt length: 6-12-18-24 instead of original
6-9-12-15-18-21-24. |
If artificial cds length is not divisible by 2, like 3 codons,
the second codon will always be from the start region etc.
Also If there are many very short original cds, the distribution
will be skewed towards more smaller artificial cds.
GRangesList of new ORFs (sorted: + strand increasing start, - strand decreasing start)
txdb <- ORFik.template.experiment()
#cds <- loadRegion(txdb, "cds")
## To get enough CDSs, just replicate them
# cds <- rep(cds, 100)
#artificial.orfs(cds)
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