initiationScore {ORFik} | R Documentation |
initiationScore tries to check how much each TIS region resembles, the average of the CDS TIS regions.
initiationScore(grl, cds, tx, reads, pShifted = TRUE, weight = "score")
grl |
a |
cds |
a |
tx |
a GrangesList of transcripts covering grl. |
reads |
ribo seq reads as |
pShifted |
a logical (TRUE), are riboseq reads p-shifted? |
weight |
a vector (default: 1L, if 1L it is identical to countOverlaps()), if single number (!= 1), it applies for all, if more than one must be equal size of 'reads'. else it must be the string name of a defined meta column in subject "reads", that gives number of times a read was found. GRanges("chr1", 1, "+", score = 5), would mean "score" column tells that this alignment region was found 5 times. |
Since this features uses a distance matrix for scoring, values are
distributed like this:
As result there is one value per ORF:
0.000: means that ORF had no reads
-1.000: means that ORF is identical to average of CDS
1.000: means that orf is maximum different than average of CDS
If a score column is defined, it will use it as weights,
see getWeights
an integer vector, 1 score per ORF, with names of grl
doi: 10.1186/s12915-017-0416-0
Other features:
computeFeaturesCage()
,
computeFeatures()
,
countOverlapsW()
,
disengagementScore()
,
distToCds()
,
distToTSS()
,
entropy()
,
floss()
,
fpkm_calc()
,
fpkm()
,
fractionLength()
,
insideOutsideORF()
,
isInFrame()
,
isOverlapping()
,
kozakSequenceScore()
,
orfScore()
,
rankOrder()
,
ribosomeReleaseScore()
,
ribosomeStallingScore()
,
startRegionCoverage()
,
startRegion()
,
stopRegion()
,
subsetCoverage()
,
translationalEff()
# Good hiting ORF ORF <- GRanges(seqnames = "1", ranges = IRanges(21, 40), strand = "+") names(ORF) <- c("tx1") grl <- GRangesList(tx1 = ORF) # 1 width p-shifted reads reads <- GRanges("1", IRanges(c(21, 23, 50, 50, 50, 53, 53, 56, 59), width = 1), "+") score(reads) <- 28 # original width cds <- GRanges(seqnames = "1", ranges = IRanges(50, 80), strand = "+") cds <- GRangesList(tx1 = cds) tx <- GRanges(seqnames = "1", ranges = IRanges(1, 85), strand = "+") tx <- GRangesList(tx1 = tx) initiationScore(grl, cds, tx, reads, pShifted = TRUE)