R/qpcrANOVARE.r
qpcrANOVARE.Rd
Analysis of variance of relative expression (\(\Delta C_T\) method) values for all factor level combinations in the experiment in which the expression level of a reference gene is used as normalizer.
qpcrANOVARE(x, numberOfrefGenes, block, alpha = 0.05, adjust = "none")
a data frame consisting of condition columns, target gene efficiency (E), target Gene Ct, reference
gene efficiency and reference gene Ct values, respectively. Each Ct in the data frame is the mean of
technical replicates. Complete amplification efficiencies of 2 was assumed in the example data for
all wells but the calculated efficienies can be used instead. NOTE: Each line belongs to a separate
individual reflecting a non-repeated measure experiment). See vignette
,
section "data structure and column arrangement" for details.
number of reference genes (1 or 2). Up to two reference genes can be handled.
column name of the blocking factor (for correct column arrangement see example data.). When a qPCR experiment is done in multiple qPCR plates, variation resulting from the plates may interfere with the actual amount of gene expression. One solution is to conduct each plate as a complete randomized block so that at least one replicate of each treatment and control is present on a plate. Block effect is usually considered as random and its interaction with any main effect is not considered.
significance level
method for adjusting p-values
A list with 4 elements:
The row data plus weighed delta Ct (wDCt) values.
The output of linear model analysis including ANOVA tables
ANOVA table based on CRD
The result table including treatments and factors, RE (Relative Expression), LCL, UCL, letter display for pair-wise comparisons and standard error with the lower and upper limits.
The qpcrANOVARE
function performs analysis of variance (ANOVA) of relative
expression (RE) values for all factor level combinations as treatments using the expression
level of a reference gene is used as normalizer. To get a reliable result, the expression of
the reference gene needs to be constant across all test samples and it expression should not
be affected by the experimental treatment under study.
Livak, Kenneth J, and Thomas D Schmittgen. 2001. Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the Double Delta CT Method. Methods 25 (4). doi:10.1006/meth.2001.1262.
Ganger, MT, Dietz GD, and Ewing SJ. 2017. A common base method for analysis of qPCR data and the application of simple blocking in qPCR experiments. BMC bioinformatics 18, 1-11.
Yuan, Joshua S, Ann Reed, Feng Chen, and Neal Stewart. 2006. Statistical Analysis of Real-Time PCR Data. BMC Bioinformatics 7 (85). doi:10.1186/1471-2105-7-85.
# If the data include technical replicates, means of technical replicates
# should be calculated first using meanTech function.
# Applying ANOVA
qpcrANOVARE(data_3factor, numberOfrefGenes = 1, block = NULL)
#> Analysis of Variance Table
#>
#> Response: wDCt
#> Df Sum Sq Mean Sq F value Pr(>F)
#> T 11 94.001 8.5456 29.188 3.248e-11 ***
#> Residuals 24 7.027 0.2928
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Relative expression table
#> Type Conc SA RE LCL UCL se Lower.se Upper.se letters
#> 1 S H A2 5.1934 3.3217 8.1197 0.1309 4.7429 5.6867 a
#> 2 S H A1 2.9690 1.8990 4.6420 0.0551 2.8577 3.0846 ab
#> 3 R H A2 1.7371 1.1110 2.7159 0.0837 1.6392 1.8409 bc
#> 4 S L A2 1.5333 0.9807 2.3973 0.0865 1.4441 1.6280 c
#> 5 R H A1 0.9885 0.6323 1.5455 0.0841 0.9325 1.0478 cd
#> 6 S L A1 0.7955 0.5088 1.2438 0.2128 0.6864 0.9219 d
#> 7 S M A2 0.7955 0.5088 1.2438 0.2571 0.6656 0.9507 d
#> 8 R M A1 0.6271 0.4011 0.9804 0.4388 0.4626 0.8500 de
#> 9 S M A1 0.4147 0.2652 0.6483 0.2540 0.3478 0.4945 ef
#> 10 R M A2 0.3150 0.2015 0.4925 0.2890 0.2578 0.3849 f
#> 11 R L A1 0.2852 0.1824 0.4459 0.0208 0.2811 0.2893 f
#> 12 R L A2 0.0641 0.0410 0.1002 0.8228 0.0362 0.1134 g
qpcrANOVARE(data_2factorBlock, block = "Block", numberOfrefGenes = 1)
#> Analysis of Variance Table
#>
#> Response: wDCt
#> Df Sum Sq Mean Sq F value Pr(>F)
#> block 1 0.0072 0.0072 0.0425 0.8404
#> T 5 20.5489 4.1098 24.1712 1.377e-05 ***
#> Residuals 11 1.8703 0.1700
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Relative expression table
#> factor1 factor2 RE LCL UCL se Lower.se Upper.se letters
#> 1 S 0.5 2.9545 2.0470 4.2644 0.0551 2.8438 3.0695 a
#> 2 R 0.5 0.9837 0.6815 1.4198 0.0841 0.9280 1.0427 b
#> 3 S 0 0.7916 0.5485 1.1426 0.2128 0.6830 0.9174 b
#> 4 R 0.25 0.6240 0.4323 0.9006 0.4388 0.4604 0.8458 bc
#> 5 S 0.25 0.4126 0.2859 0.5956 0.2540 0.3460 0.4920 cd
#> 6 R 0 0.2838 0.1966 0.4096 0.0208 0.2797 0.2879 d