qpcr's Introduction

qpcR

Calculate relative gene expression values of raw qPCR data. Base R. No dependencies. Detailed documentation will follow soon.

Quick start

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")

Input data

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.

Output

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

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