Package 'CCWeights'

Title: Perform Weighted Linear Regression for Calibration Curve
Description: Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. In addition, a 'shiny' App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements.
Authors: Yonghui Dong
Maintainer: Yonghui Dong <[email protected]>
License: GPL-3
Version: 0.1.6
Built: 2025-02-02 03:56:14 UTC
Source: https://github.com/yonghuidong/ccweights

Help Index

Perform Calibration

Description

Perform calibration

Usage

doCalibration(DF, weights = NULL)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'
weights

default is NULL

Value

dataframe, the quantification result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, "unknown"), each = 3)
Response <- c(133, 156, 177, 6650, 7800, 8850, 13300, 15600, 17700, 156, 1450, 1400)
DF <- cbind.data.frame(Concentration = Concentration, Response = Response)
result <- doCalibration(DF)

Evaluate Different Weighting Factors

Description

Evaluate different weighting factors.

Usage

doEvaluation(DF, p = 0.05, userWeights = NULL)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'
p

p-value, default is 0.05
userWeights

user defined weights in linear regression, default is NULL. User can easily define weights, e.g., "1/x", "1/x^2", "1/y"

Value

dataframe, weighting factor evaluation result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, 500), each = 3)
Response <- c(133, 156, 177, 1300, 1450, 1600, 4000, 3881, 3700, 140000, 139000, 140000)
DF <- cbind.data.frame(Concentration = Concentration, Response = Response)
result <- doEvaluation(DF)

Perform F Test

Description

perform F test to evaluate homoscedasticity.

Usage

doFtest(DF, p = 0.01, lower.tail = FALSE)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'
p

p-value
lower.tail

default is FALSE

Value

dataframe, F test result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, 500), each = 3)
Response <- c(133, 156, 177, 1300, 1450, 1600, 4000, 3881, 3700, 140000, 139000, 140000)
DF <- cbind.data.frame(Concentration, Response)
result <- doFtest(DF, p = 0.01)

Perform Weighted Linear Regression

Description

Perform weighted linear regression and evaluate by using summed residual.

Usage

doWlm(DF, weights = NULL)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'
weights

the weights used in linear regression, default is NULL. User can easily define weights, e.g., "1/x", "1/x^2", "1/y"

Value

list, weighted linear regression result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, 500), each = 3)
Response <- c(133, 156, 177, 1300, 1450, 1600, 4000, 3881, 3700, 140000, 139000, 140000)
DF <- cbind.data.frame(Concentration = Concentration, Response = Response)
result <- doWlm(DF, weights = "1/x^2")

expData

Description

Two example data set: one with internal standards (IS), and one without IS

Usage

expData

Format

A list with 2 data frames:

noSTD

the example data without IS

STD

the example data with IS

Run CCWeights Gui

Description

Run CCWeights Gui.

Usage

runGui()

Value

Gui

Author(s)

Yonghui Dong

Examples

if(interactive()){}