kozakSequenceScore {ORFik} | R Documentation |
The closer the sequence is to the Kozak sequence the higher the score, based on the experimental pwms from article referenced. Minimum score is 0 (worst correlation), max is 1 (the best base per column was chosen).
kozakSequenceScore(grl, faFile, species = "human", include.N = FALSE)
grl |
a |
faFile |
a FaFile from the fasta file, see ?FaFile. Can also be path to fastaFile with fai file in same dir. |
species |
("human"), which species to use, currently supports human, zebrafish and mouse (m. musculus). You can also specify a pfm for your own species. Syntax of pfm is an rectangular integer matrix, where all columns must sum to the same value, normally 100. See example for more information. Rows are in order: c("A", "C", "G", "T") |
include.N |
logical (F), if TRUE, allow N bases to be counted as hits, score will be average of the other bases. If True, N bases will be added to pfm, automaticly, so dont include them if you make your own pfm. |
a numeric vector with values between 0 and 1
an integer vector, one score per orf
doi: https://doi.org/10.1371/journal.pone.0108475
Other features: computeFeaturesCage
,
computeFeatures
,
disengagementScore
,
distToCds
, distToTSS
,
entropy
, floss
,
fpkm_calc
, fpkm
,
fractionLength
,
initiationScore
,
insideOutsideORF
, isInFrame
,
isOverlapping
, orfScore
,
rankOrder
,
ribosomeReleaseScore
,
ribosomeStallingScore
,
subsetCoverage
,
translationalEff
# Usually the ORFs are found in orfik, which makes names for you etc. # Here we make an example from scratch seqName <- "Chromosome" ORF1 <- GRanges(seqnames = seqName, ranges = IRanges(c(1007, 1096), width = 60), strand = c("+", "+")) ORF2 <- GRanges(seqnames = seqName, ranges = IRanges(c(400, 100), width = 30), strand = c("-", "-")) ORFs <- GRangesList(tx1 = ORF1, tx2 = ORF2) ORFs <- makeORFNames(ORFs) # need ORF names # get faFile for sequences faFile <- FaFile(system.file("extdata", "genome.fasta", package = "ORFik")) kozakSequenceScore(ORFs, faFile) # For more details see vignettes.