This function plot different isomiRs proportion for each sample. It can show trimming events at both side, additions and nucleotides changes.

isoPlot(ids, type = "iso5", column = NULL, use = NULL, nts = FALSE)

Arguments

ids

Object of class IsomirDataSeq.

type

String (iso5, iso3, add, snv, all) to indicate what isomiRs to use for the plot. See details for explanation.

column

String indicating the column in colData to color samples.

use

Character vector to only use these isomiRs for the plot. The id used is the rownames that comes from using isoCounts with all the arguments on TRUE.

nts

Boolean to indicate whether plot positions of nucleotides changes when showing single nucleotides variants.

Value

ggplot2::ggplot() Object showing different isomiRs changes at different positions.

Details

There are four different values for type parameter. To plot trimming at 5' or 3' end, use type="iso5" or type="iso3". Get a summary of all using type="all". In this case, it will plot 3 positions at both side of the reference position described at miRBase site. Each position refers to the % of sequences that start/end before or after the miRBase reference. The color indicates the sample group. The size of the point is proportional to the abundance considering the total as all the sequences in the sample. The position at y is the % of different sequences considering the total as all sequences with changes for the specific isomiR showed.

Same logic applies to type="add" and type="subs". However, when type="add", the plot will refer to addition events from the 3' end of the reference position. Note that this additions don't match to the precursor sequence, they are non-template additions. In this case, only 3 positions after the 3' end will appear in the plot. When type="subs", it will appear one position for each nucleotide in the reference miRNA. Points will indicate isomiRs with nucleotide changes at the given position. When type="all" a colar coordinate map will show the abundance of each isomiR type in a single plot. Note the position is relatively to the sequence not the miRNA.

Examples

data(mirData) isoPlot(mirData)
#> Using 17048 isomiRs.
#> Joining, by = "id"