Calculate dilutions from predicted concentrations

Usage

qp_dilute(x, ...)

# S3 method for data.frame
qp_dilute(
  x,
  target_conc = NULL,
  target_vol = 15,
  remove_standards = FALSE,
  pipette_vol_compat = TRUE,
  ...
)

# S3 method for list
qp_dilute(
  x,
  target_conc = NULL,
  target_vol = 15,
  remove_standards = FALSE,
  ...
)

Arguments

x: A data.frame or list containing a data.frame named qp with a column named .pred_conc or .pred_conc_mean. If both, will favor .pred_conc_mean.
...: Unused
target_conc: Numeric vector. Target concentration in (mg/mL) protein. If length == 1, recycled.
target_vol: Target volume in uL. If length == 1, recycled.
remove_standards: Boolean. Should standards be removed from results?
pipette_vol_compat: Boolean. Shold returned numbers be rounded to the typically precision of a pipette?

Value

Same as input, with the volumes of lysate and volumes of diluent to add.

Examples


df <- data.frame(.pred_conc = 1)
qp_dilute(df, target_conc = 0.5, target_vol = 30)
#>   .pred_conc sample_to_add add_to .target_conc .target_vol
#> 1          1            15     15          0.5          30


# Many sample and target concentrations
df2 <- data.frame(.pred_conc = 1:3)
qp_dilute(df2, target_conc = c(0.1, 0.4, 0.8), target_vol = 30)
#>   .pred_conc sample_to_add add_to .target_conc .target_vol
#> 1          1             3     27          0.1          30
#> 2          2             6     24          0.4          30
#> 3          3             8     22          0.8          30

# Takes a list, so long as it has a data.frame named qp as one of the items:
ls <- list(qp = data.frame(.pred_conc = 3))
qp_dilute(ls, target_conc = 0.5, target_vol = 30)
#> $qp
#>   .pred_conc sample_to_add add_to .target_conc .target_vol
#> 1          3             5     25          0.5          30
#>