Calculate relative gene expression values of raw qPCR data. Base R. No dependencies. Detailed documentation will follow soon.
library(devtools)
devtools::install_github("mschemmel/qpcR")
# load example data
qpcRdata <- read.table(system.file("extdata", "example2.tsv", package = "qpcR"), sep = "\t", head = TRUE)
# get mean relative expression
qpcR(qpcRdata, hkg = "HKG", groups = "dpi")
The minimal structure of the input data has to contain following columns: gene
, treatment
, cq
. Primer efficiency
values are optional.
Column | Description | Note |
---|---|---|
gene |
investigated genes | |
treatment |
variable to compare | |
cq |
cq value measured by qPCR machine | |
efficiency |
primer efficiency values (%) | (optional) assumed to be 100 % if not provided |
If cq
contains NA, brep
, trep
or both columns are needed to properly exclude samples.
Column | Description |
---|---|
brep |
number of biological replicate |
trep |
number of technical replicate |
Example datasets can be found in the inst/extdata
folder.
qpcR outputs a data frame with following columns:
Column | Description |
---|---|
treatment | treatments used in your experiment |
gene | all investigated genes except housekeeping gene(s) |
dpi | your group(s) variable (if input data was grouped) |
rexpr.mean | mean expression value |
rexpr.sd | standard deviation of expression values |
rexpr.se | standard error of expression values |
rexpr.n | number observations per gene x group(s) x treatment variables |