apply_delta_delta_ct.Rd
This function will calculate the delta delta Ct metric for all applicable observations in a data.frame
by applying the calc_delta_delta_ct
function. The data.frame must have the following columns:
'location_id', 'sample_date', 'target_name', and 'ct_value'. The relevant target_names and associated reference_names
must be provided. The result is a data.frame containing a 'delta_delta_ct' column which can be merge into the source data.frame.
apply_delta_delta_ct(
df,
target_names,
reference_names,
pae_names = NULL,
pae_values = NULL
)
A data.frame containing the following columns: 'location_id', 'sample_date', 'target_name', and 'ct_value'.
Character vector giving the names of the target genes.
Character vector giving the names of the reference genes associated with each target gene.
Character vector giving the names of the target genes and reference genes for which the percentile amplification efficiency has been estimated. Default is NULL.
A numeric scalar giving the estimated PCR amplification efficiency for each of the names in pae_names
. Defaults is NULL, which assumes 100% efficiency.
data.frame
if (FALSE) {
pae <- apply_amplification_efficiency(template_standard_curve)
ddct_standard <- apply_delta_delta_ct(df = template_es_data,
target_names = c('target_1', 'target_2', 'target_3'),
reference_names = rep('target_0', 3))
ddct_adjusted <- apply_delta_delta_ct(df = template_es_data,
target_names = c('target_1', 'target_2', 'target_3'),
reference_names = rep('target_0', 3),
pae_names = pae$target_name,
pae_values = pae$mean)
}