kozakHeatmap {ORFik} | R Documentation |
Given sequences, DNA or RNA. And some score, ribo-seq fpkm, TE etc. Create a heatmap divided per letter in seqs, by how strong the score is.
kozakHeatmap( seqs, rate, start = 1, stop = max(nchar(seqs)), center = ceiling((stop - start + 1)/2), min.observations = ">q1", skip.startCodon = FALSE, xlab = "TIS", type = "ribo-seq" )
seqs |
the sequences (character vector, DNAStringSet) |
rate |
a scoring vector (equal size to seqs) |
start |
position in seqs to start at (first is 1), default 1. |
stop |
position in seqs to stop at (first is 1), default max(nchar(seqs)), that is the longest sequence length |
center |
position in seqs to center at (first is 1), center will be +1 in heatmap |
min.observations |
How many observations per position per letter to accept? numeric or quantile, default (">q1", bigger than quartile 1 (25 percentile)). You can do (10), to get all with more than 10 observations. |
skip.startCodon |
startCodon is defined as after centering (position 1, 2 and 3). Should they be skipped ? default (FALSE). Not relevant if you are not doing Translation initiation sites (TIS). |
xlab |
Region you are checking, default (TIS) |
type |
What type is the rate scoring ? default (ribo-seq) |
It will create blocks around the highest rate per position
a ggplot of the heatmap
## Not run: if (requireNamespace("BSgenome.Hsapiens.UCSC.hg19")) { txdbFile <- system.file("extdata", "hg19_knownGene_sample.sqlite", package = "GenomicFeatures") #Extract sequences of Coding sequences. cds <- loadRegion(txdbFile, "cds") tx <- loadRegion(txdbFile, "mrna") # Get region to check kozakRegions <- startRegionString(cds, tx, BSgenome.Hsapiens.UCSC.hg19::Hsapiens , upstream = 4, 5) # Some toy ribo-seq fpkm scores on cds set.seed(3) fpkm <- sample(1:115, length(cds), replace = TRUE) kozakHeatmap(kozakRegions, fpkm, 1, 9, skip.startCodon = F) } ## End(Not run)