std_curve_fit: Create a Standard Curve From Known Data

In rforbiochemists/standard: Simplified Fitting and Use of Standard Curves

Create a Standard Curve From Known Data

Description

Create a Standard Curve From Known Data

Usage

std_curve_fit(data, conc, resp)

Arguments

data	A data.frame that contains the columns for concentration and observed response for the standard curve.
conc	Name of the column that contains the concentration for the standard curve.
resp	Name of the column that contains the response values for the standard curve.

Value

A linear model ( lm() ) object to be used as a standard curve, for use with standard::std_curve_calc() broom::augment() or stats::predict().

Examples

library(standard)

# Protein concentrations of the standards used in the assay
prot <- c(
  0.000, 0.016, 0.031, 0.063, 0.125, 0.250, 0.500, 1.000,
  0.000, 0.016, 0.031, 0.063, 0.125, 0.250, 0.500, 1.000
)

# absorbance readings from the standards used in the assay
abs <- c(
  0.329, 0.352, 0.349, 0.379, 0.417, 0.491, 0.668, 0.956,
  0.327, 0.341, 0.355, 0.383, 0.417, 0.446, 0.655, 0.905
)
assay_data <- data.frame(
  Protein = prot,
  Absorbance = abs
)

# unknown concentrations
unk <- c(0.554, 0.568, 0.705)


assay_data |>
  std_curve_fit(Protein, Absorbance) |>
  plot()

rforbiochemists/standard documentation built on Oct. 29, 2023, 11:14 a.m.