metaheatmap_psite: Ribosome occupancy metaheatmaps at single-nucleotide...

In LabTranslationalArchitectomics/riboWaltz: Optimization of ribosome P-site positioning in ribosome profiling data

Ribosome occupancy metaheatmaps at single-nucleotide resolution.

Description

This function generates heatmap-like metaprofiles (metaheatmaps) displaying the abundance of P-sites around the start and the stop codon of annotated CDSs for multiple samples. It works similarly to metaprofile_psite but the intensity of signal is represented by a continuous color scale rather than by the height of a line chart. This graphical option always returns one heatmap displaying all the specified samples thus optimizing the visualization of several profiles in a small area.

Usage

metaheatmap_psite(
  data,
  annotation,
  sample,
  multisamples = "average",
  scale_factors = "auto",
  transcripts = NULL,
  length_range = NULL,
  cl = 100,
  utr5l = 25,
  cdsl = 50,
  utr3l = 25,
  colour = "black",
  log_colour = FALSE
)

Arguments

data	Either list of data tables or GRangesList object from psite_info.
annotation	Data table as generated by create_annotation.
sample	Either character string, character string vector or named list of character string(s)/character string vector(s) specifying the name of the sample(s) and replicate(s) of interest. If a list is provided, each element of the list is considered as an independent sample associated with one ore multiple replicates. Multiple samples and replicates are handled according to multisamples.
multisamples	Either "average" or "independent". It specifies how to handle multiple samples and replicates stored in sample: if sample is a character string vector and multisamples is set to "average" the elements of the vector are considered as replicates of one sample. if sample is a character string vector and multisamples is set to "independent", each element of the vector is analysed independently of the others. if sample is list, multisamples must be set to "average". Each element of the list is analysed independently of the others, its replicates averaged and its name reported in the plot. Note: when this parameter is set to "average" the intensity of the profile associated with each sample reports the nucleotide-specific mean signal computed across the replicates. Default is "average".
scale_factors	Either "auto", a named numeric vector or "none". It specifies how metaprofiles should be scaled before merging multiple replicates (if any): "auto": each metaprofile is scaled so that the area under the curve is 1. named numeric vector: scale_factors must be the same length of unlisted sample and each scale factor must be named after the corresponding string in unlisted sample. No specific order is required. Each metaprofile is multiplied by the matching scale factor. "none": no scaling is applied. Default is "auto".
transcripts	Character string vector listing the name of transcripts to be included in the analysis. Default is NULL, i.e. all transcripts are used. Please note: transcripts with either 5' UTR, coding sequence or 3' UTR shorter than utr5l, 2*cdsl and utr3l, respectively, are automatically discarded.
length_range	Integer or integer vector for restricting the plot to a chosen range of read lengths. Default is NULL, i.e. all read lengths are used. If specified, this parameter prevails over cl.
cl	Integer value in 1,100 specifying a confidence level for restricting the plot to an automatically-defined range of read lengths. The new range is computed according to the most frequent read lengths, which accounts for the cl% of the sample and is defined by discarding the (100-cl)% of read lengths falling in the tails of the read lengths distribution. If multiple samples are analysed, a single range of read lengths is computed such that at least the cl% of all sample are represented. Default is 100.
utr5l	Positive integer specifying the length (in nucleotides) of the 5' UTR region flanking the start codon to be considered in the analysis. Default is 25.
cdsl	Positive integer specifying the length (in nucleotides) of the CDS regions flanking both the start and stop codon to be considered in the analysis. Default is 50.
utr3l	Positive integer specifying the length (in nucleotides) of the 3' UTR region flanking the stop codon to be considered in the analysis. Default is 25.
colour	Character string specifying the colour of the plot. The colour scheme is as follow: tiles corresponding to the lowest signal are always white, tiles corresponding to the highest signal are of the specified colour and the progression between these two colours follows either linear or logarithmic gradients (see log_colour).Default is "black".
log_colour	Logical value whether to use a logarithmic colour scale (strongly suggested in case of large signal variations). Default is FALSE.

Value

List containing: one or more ggplot object(s) and the data table with the corresponding x- and y-axis values ("plot_dt"); an additional data table with raw and scaled number of P-sites per codon in the selected region for each sample ("count_dt").

Examples

## data(reads_list)
## data(mm81cdna)
##
## ## Generate fake samples and replicates
## for(i in 2:6){
##   samp_name <- paste0("Samp", i)
##   set.seed(i)
##   reads_list[[samp_name]] <- reads_list[["Samp1"]][sample(.N, 5000)]
## }
##
## ## Compute and add p-site details
## psite_offset <- psite(reads_list, flanking = 6, extremity = "auto")
## reads_psite_list <- psite_info(reads_list, psite_offset)
##
## ## Define the list of samples and replicate to use as input
## input_samples <- list("S1" = c("Samp1", "Samp2"),
##                       "S2" = c("Samp3", "Samp4", "Samp5"),
##                       "S3" = c("Samp6"))
##
## Generate metaheatmap
## example_metaheatmap <- metaheatmap_psite(reads_psite_list, mm81cdna,
##                                          sample = input_samples,
##                                          multisamples = "average",
##                                          utr5l = 20, cdsl = 40, utr3l = 20,
##                                          colour = "#333f50"))

LabTranslationalArchitectomics/riboWaltz documentation built on Jan. 17, 2024, 12:18 p.m.