data_2factorBlock

A sample qPCR data set with blocking factor. Each line belongs to a separate individual (non-repeated measure experiment).

internal

Various methods are employed for statistical analysis and graphical presentation of real-time PCR (quantitative PCR or qPCR) data. 'rtpcr' handles amplification efficiency calculation, statistical analysis and graphical representation of real-time PCR data based on up to two reference genes. By accounting for amplification efficiency values, 'rtpcr' was developed using a general calculation method described by Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and Pfaffl methods. Based on the experimental conditions, the functions of the 'rtpcr' package use t-test (for experiments with a two-level factor), analysis of variance (ANOVA), analysis of covariance (ANCOVA) or analysis of repeated measure data to calculate the fold change (FC, Delta Delta Ct method) or relative expression (RE, Delta Ct method). The functions further provide standard errors and confidence intervals for means, apply statistical mean comparisons and present significance. To facilitate function application, different data sets were used as examples and the outputs were explained. ‘rtpcr’ package also provides bar plots using various controlling arguments. The 'rtpcr' package is user-friendly and easy to work with and provides an applicable resource for analyzing real-time PCR data.

Ghader Mirzaghaderi

rtpcr

qPCR Data Analysis

data_2factorBlock function

A data frame with 18 observations and 8 variables:<dl>
 <dt>factor1</dt>
<dd>First experimental factor</dd> <dt>factor2</dt>
<dd>Second experimental factor</dd> <dt>block</dt>
<dd>Second experimental factor</dd> <dt>Rep</dt>
<dd>Biological replicates</dd> <dt>E_PO</dt>
<dd>Mean amplification efficiency of PO gene</dd> <dt>Ct_PO</dt>
<dd>Ct values of PO gene. Each is the mean of technical replicates</dd> <dt>E_GAPDH</dt>
<dd>Mean amplification efficiency of GAPDH gene</dd> <dt>Ct_GAPDH</dt>
<dd>Ct values of GAPDH gene. Each is the mean of technical replicates</dd>
</dl>

Format

Sample data (two factor with blocking factor) — data_2factorBlock

A data frame with 18 observations and 8 variables:<dl>
 <dt>factor1</dt>
<dd>First experimental factor</dd>

 <dt>factor2</dt>
<dd>Second experimental factor</dd>

 <dt>block</dt>
<dd>Second experimental factor</dd>

 <dt>Rep</dt>
<dd>Biological replicates</dd>

 <dt>E_PO</dt>
<dd>Mean amplification efficiency of PO gene</dd>

 <dt>Ct_PO</dt>
<dd>Ct values of PO gene. Each is the mean of technical replicates</dd>

 <dt>E_GAPDH</dt>
<dd>Mean amplification efficiency of GAPDH gene</dd>

 <dt>Ct_GAPDH</dt>
<dd>Ct values of GAPDH gene. Each is the mean of technical replicates</dd>


</dl>

data_2factorBlock: Sample data (two factor with blocking factor)

Description

Usage

Arguments

Format