Calculate Coefficient of Variation for Each Target for a Set of AQ Runs

Calculates intra-plate coefficient of variation (CV) for each target for a single AQ run or intra- and inter-plate CV for a set of AQ runs. By default the function will output CVs for sample types SC (AQSC) and IPC (CAL). In the future, we might add the ability to also output CVs for samples that are grouped using a provided sample name pattern. Function input is the output of loadNULISAseq or a list of loadNULISAseq outputs. CVs are calculated directly on the AQ data in aM units. Values outside of the dynamic range are excluded from CV calculation.

CV_AQ(runs, exclude_outside_DR = TRUE)

Arguments

runs

A named list of a single run data output from laodNULISAseq() function or a named list of these outputs for multiple runs.

exclude_outside_DR

Logical. Default is TRUE. Should values outside the dynamic range (i.e., values below LLOQ or above ULOQ) be excluded before calculating CV?

Value

A nested list containing CV information. List elements include:

run_intraCV

A list with the same names as runs. Each run has a sublist that includes a intraCV data frame with targets in rows and samples as columns, and n_samples vector which gives number of sample replicates corresponding to each column in intraCV.

average_intraCV

Summarizes intraCV across runs by taking the average of the run-specific CVs. This sublist also includes a intraCV data frame with targets in rows and samples as columns, and n_samples vector which gives average number of sample replicates per run corresponding to each column in intraCV. If only a single run is input, combined_intraCV will be identical to run_intraCV.

interCV

If multiple runs are input, the interCV list is output. This gives the inter-plate CV calculated on the pooled replicates. Note this is not a component inter-plate CV but a total CV across all runs. This list includes a interCV data frame with targets in rows and samples as columns, and n_samples vector which gives number of sample replicates corresponding to each column in interCV.