Apply the delta delta Ct calculation to a data.frame
Source:R/apply_delta_delta_ct.R
apply_delta_delta_ct.RdThis 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
pae_names. Defaults is NULL, which assumes 100% efficiency.
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)
#> location_id sample_date target_name delta_delta_ct
#> 1 1 2017-06-11 target_1 1.000000
#> 2 1 2017-06-15 target_1 23.056872
#> 3 1 2017-06-27 target_1 41.051045
#> 4 1 2017-06-28 target_1 44.685668
#> 5 1 2017-07-04 target_1 6.698673
#> 6 1 2017-07-08 target_1 10.677717