Calculate delta cq (\(\Delta Cq\)) to normalize quantification cycle (log2-fold) data within sample_id.

This function implements relative quantification by the delta Cq method. For each sample, the Cq values of all targets (e.g. genes, probes, primer sets) are compared to one or more reference target ids specified in `ref_target_ids`.

calculate_deltacq_bysampleid(cq_df, ref_target_ids, norm_function = median)

Arguments

cq_df	a data frame containing columns `sample_id`, value_name (default `cq`) and tid_name (default `target_id`). Crucially, sample_id should be the same for different technical replicates measuring identical reactions in different wells of the plate, but differ for different biological and experimental replicates. See tidyqpcr vignettes for examples.
ref_target_ids	names of targetss to normalize by, i.e. reference genes, hydrolysis probes, or primer sets. This can be one reference target id, a selection of multiple target ids, or even all measured target ids. In the case of all of them, the delta Cq value would be calculated relative to the median (or other `norm_function`) of all measured targets.
norm_function	Function to use to calculate the value to normalize by on given scale. Default is median, alternatively could use mean.

Value

data frame like cq_df with three additional columns:

ref_cq	summary (median/mean) cq value for reference target ids
delta_cq	normalized value, \(\Delta Cq\)
rel_abund	normalized ratio, \(2^(-\Delta Cq)\)