rtpcr (version 2.0.1)

qpcrTTESTplot: Bar plot of the average fold change (\(\Delta \Delta C_T\) method) of target genes

Description

Bar plot of the fold change (\(\Delta \Delta C_T\) method) values for for any number of target genes under a two-level conditional experimental (e.g. control and treatment).

Usage

qpcrTTESTplot(
  x,
  order = "none",
  numberOfrefGenes,
  paired = FALSE,
  var.equal = TRUE,
  width = 0.5,
  fill = "skyblue",
  y.axis.adjust = 0,
  y.axis.by = 2,
  letter.position.adjust = 0.3,
  ylab = "Average Fold Change",
  xlab = "none",
  fontsize = 12,
  fontsizePvalue = 7,
  axis.text.x.angle = 0,
  axis.text.x.hjust = 0.5,
  errorbar = "se"
)

Value

Bar plot of the average fold change for target genes along with the significance and the 95 percent CI as error bars.

Arguments

x

a data frame. The data frame consists of 4 columns belonging to condition levels, E (efficiency), genes and Ct values, respectively. Each Ct in the following data frame is the mean of technical replicates. Complete amplification efficiencies of 2 is assumed here for all wells but the calculated efficienies can be used we well. We use this data set for fold change expression analysis of the target genes in treatment condition compared to normal condition. See vignette for details.

order

a vector determining genes order on the output graph.

numberOfrefGenes

number of reference genes. Up to two reference genes can be handled.

paired

a logical indicating whether you want a paired t-test.

var.equal

a logical variable indicating whether to treat the two variances as being equal. If TRUE then the pooled variance is used to estimate the variance otherwise the Welch (or Satterthwaite) approximation to the degrees of freedom is used.

width

a positive number determining bar width.

fill

specify the fill color for the columns of the bar plot.

y.axis.adjust

a negative or positive value for reducing or increasing the length of the y axis.

y.axis.by

determines y axis step length

letter.position.adjust

adjust the distance between the signs and the error bars.

ylab

the title of the y axis

xlab

the title of the x axis

fontsize

fonts size of the plot

fontsizePvalue

font size of the pvalue labels

axis.text.x.angle

angle of x axis text

axis.text.x.hjust

horizontal justification of x axis text

errorbar

Type of error bar, can be se or ci.

Author

Ghader Mirzaghaderi

Details

The qpcrTTESTplot function applies a t.test based analysis to any number of target genes along with one or two reference gene(s), that have been evaluated under control and treatment conditions. It returns the bar plot of the fold change (FC) values for target genes along with the 95% CI and significance. Sampling may be unpaired or paired. Unpaired and paired samples are commonly analyzed using unpaired and paired t-test, respectively.Paired samples in quantitative PCR refer to two sample data that are collected from one set of individuals at two different conditions, for example before and after a treatment or at two different time points. While for unpaired samples, two sets of individuals are used: one under untreated and the other set under treated condition. Paired samples allow to compare gene expression changes within the same individual, reducing inter-individual variability.

Examples

# See a sample data frame
data_ttest


qpcrTTESTplot(data_ttest, 
              numberOfrefGenes = 1,
              errorbar = "ci")


# Producing the plot
qpcrTTESTplot(data_ttest,
              numberOfrefGenes = 1,
              order = c("C2H2-01", "C2H2-12", "C2H2-26"),
              paired = FALSE,
              var.equal = TRUE,
              width = 0.5,
              fill = "skyblue",
              y.axis.adjust = 0,
              y.axis.by = 2,
              letter.position.adjust = 0.3,
              ylab = "Fold Change in Treatment vs Control",
              xlab = "Gene",
              errorbar = "se")