apply_delta_delta_ct {WES} | R Documentation |
Apply the delta delta Ct calculation to a data.frame
Description
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.
Usage
apply_delta_delta_ct(
df,
target_names,
reference_names,
pae_names = NULL,
pae_values = NULL
)
Arguments
df |
A data.frame containing the following columns: 'location_id', 'sample_date', 'target_name', and 'ct_value'. |
target_names |
Character vector giving the names of the target genes. |
reference_names |
Character vector giving the names of the reference genes associated with each target gene. |
pae_names |
Character vector giving the names of the target genes and reference genes for which the percentile amplification efficiency has been estimated. Default is NULL. |
pae_values |
A numeric scalar giving the estimated PCR amplification efficiency for each of the names in |
Value
data.frame
Examples
pae <- apply_amplification_efficiency(template_WES_standard_curve)
ddct_standard <- apply_delta_delta_ct(df = template_WES_data,
target_names = c('target_1', 'target_2', 'target_3'),
reference_names = rep('target_0', 3))
ddct_adjusted <- apply_delta_delta_ct(df = template_WES_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)
head(ddct_adjusted)