pcr_ddct: Calculate the delta_delta_ct model

In pcr: Analyzing Real-Time Quantitative PCR Data

Description

Uses the C_T values and a reference gene and a group to calculate the delta delta C_T model to estimate the normalized relative expression of target genes.

Usage

pcr_ddct(
  df,
  group_var,
  reference_gene,
  reference_group,
  mode = "separate_tube",
  plot = FALSE,
  ...
)

Arguments

df	A data.frame of C_T values with genes in the columns and samples in rows rows
group_var	A character vector of a grouping variable. The length of this variable should equal the number of rows of df
reference_gene	A character string of the column name of a control gene
reference_group	A character string of the control group in group_var
mode	A character string of; 'separate_tube' (default) or 'same_tube'. This is to indicate whether the different genes were run in separate or the same PCR tube
plot	A logical (default is FALSE)
...	Arguments passed to customize plot

Details

The comparative C_T methods assume that the cDNA templates of the gene/s of interest as well as the control/reference gene have similar amplification efficiency. And that this amplification efficiency is near perfect. Meaning, at a certain threshold during the linear portion of the PCR reaction, the amount of the gene of the interest and the control double each cycle. Another assumptions is that, the expression difference between two genes or two samples can be captured by subtracting one (gene or sample of interest) from another (reference). This final assumption requires also that these references don't change with the treatment or the course in question.

Value

A data.frame of 8 columns:

• group The unique entries in group_var

• gene The column names of df. reference_gene is dropped

• normalized The C_T value (or the average C_T value) of target genes after subtracting that of the reference_gene

• calibrated The normalized average C_T value of target genes after subtracting that of the reference_group

• relative_expression The expression of target genes normalized by a reference_gene and calibrated by a reference_group

• error The standard deviation of the relative_expression

• lower The lower interval of the relative_expression

• upper The upper interval of the relative_expression

When plot is TRUE, returns a bar graph of the relative expression of the genes in the column and the groups in the column group. Error bars are drawn using the columns lower and upper. When more one gene are plotted the default in dodge bars. When the argument facet is TRUE a separate panel is drawn for each gene.

Examples

## locate and read raw ct data
fl <- system.file('extdata', 'ct1.csv', package = 'pcr')
ct1 <- read.csv(fl)

# add grouping variable
group_var <- rep(c('brain', 'kidney'), each = 6)

# calculate all values and errors in one step
pcr_ddct(ct1,
         group_var = group_var,
         reference_gene = 'GAPDH',
         reference_group = 'brain')

# return a plot
pcr_ddct(ct1,
         group_var = group_var,
         reference_gene = 'GAPDH',
         reference_group = 'brain',
         plot = TRUE)

pcr documentation built on April 1, 2020, 9:07 a.m.