dispersion_est {pmartR}

Diagnostic plot for seqData

Description

For generating statistics for 'seqData' objects

Usage

dispersion_est(
  omicsData,
  method,
  interactive = FALSE,
  x_lab = NULL,
  x_lab_size = 11,
  x_lab_angle = NULL,
  y_lab = NULL,
  y_lab_size = 11,
  title_lab = NULL,
  title_lab_size = 14,
  legend_lab = NULL,
  legend_position = "right",
  bw_theme = TRUE,
  palette = NULL,
  point_size = 0.2,
  custom_theme = NULL
)

Arguments

omicsData

seqData object used to terst dispersions

method

either "DESeq2", "edgeR", or "voom" for testing dispersion

interactive

Logical. If TRUE produces an interactive plot.

x_lab

A character string specifying the x-axis label when the metric argument is NULL. The default is NULL in which case the x-axis label will be "count".

x_lab_size

An integer value indicating the font size for the x-axis. The default is 11.

x_lab_angle

An integer value indicating the angle of x-axis labels.

y_lab

A character string specifying the y-axis label. The default is NULL in which case the y-axis label will be the metric selected for the metric argument.

y_lab_size

An integer value indicating the font size for the y-axis. The default is 11.

title_lab

A character string specifying the plot title when the metric argument is NULL.

title_lab_size

An integer value indicating the font size of the plot title. The default is 14.

legend_lab

A character string specifying the legend title.

legend_position

A character string specifying the position of the legend. Can be one of "right", "left", "top", or "bottom". The default is "right".

bw_theme

Logical. If TRUE uses the ggplot2 black and white theme.

palette

A character string indicating the name of the RColorBrewer palette to use. For a list of available options see the details section in RColorBrewer.

point_size

An integer specifying the size of the points. The default is 0.2.

custom_theme

a ggplot 'theme' object to be applied to non-interactive plots, or those converted by plotly::ggplotly().

Details

DESeq2 option requires package "survival" to be available.

Value

plot result

References

Robinson MD, McCarthy DJ, Smyth GK (2010). “edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.” Bioinformatics, 26(1), 139-140. doi: 10.1093/bioinformatics/btp616.

Love, M.I., Huber, W., Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 Genome Biology 15(12):550 (2014)

Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 43(7), e47.

Examples

library(pmartRdata)
myseqData <- group_designation(omicsData = rnaseq_object, main_effects = "Virus")
dispersion_est(omicsData = myseqData, method = "edgeR")
dispersion_est(omicsData = myseqData, method = "DESeq2")
dispersion_est(omicsData = myseqData, method = "voom")