BASiCS_ShowFit: Plotting the trend after Bayesian regression

Description Usage Arguments Value Author(s) References Examples

View source: R/BASiCS_ShowFit.R

Description

Plotting the trend after Bayesian regression using a BASiCS_Chain object

Usage

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BASiCS_ShowFit(
  object,
  xlab = "log(mu)",
  ylab = "log(delta)",
  pch = 16,
  smooth = TRUE,
  variance = 1.2,
  colour = "dark blue",
  markExcludedGenes = TRUE,
  GenesSel = NULL,
  colourGenesSel = "dark red",
  Uncertainty = TRUE
)

Arguments

object

an object of class BASiCS_Chain

xlab

As in par.

ylab

As in par.

pch

As in par. Default value pch = 16.

smooth

Logical to indicate wether the smoothScatter function is used to plot the scatter plot. Default value smooth = TRUE.

variance

Variance used to build GRBFs for regression. Default value variance = 1.2

colour

colour used to denote genes within the scatterplot. Only used when smooth = TRUE. Default value colour = "dark blue".

markExcludedGenes

Whether or not lowly expressed genes that were excluded from the regression fit are included in the scatterplot. Default value markExcludedGenes = TRUE.

GenesSel

Vector of gene names to be highlighted in the scatterplot. Only used when smooth = TRUE. Default value GenesSel = NULL.

colourGenesSel

colour used to denote the genes listed in GenesSel within the scatterplot. Default value colourGenesSel = "dark red".

Uncertainty

logical indicator. If true, statistical uncertainty around the regression fit is shown in the plot.

Value

A ggplot2 object

Author(s)

Nils Eling eling@ebi.ac.uk

Catalina Vallejos cnvallej@uc.cl

References

Eling et al (2018). Cell Systems https://doi.org/10.1016/j.cels.2018.06.011

Examples

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BASiCS documentation built on April 16, 2021, 6 p.m.