Title: Easy Interface to Effective Concentration Calculations
Version: 1.0.1
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>
Description: Because fungicide resistance is an important phenotypic trait for fungi and oomycetes, it is necessary to have a standardized method of statistically analyzing the Effective Concentration (EC) values. This package is designed for those who are not terribly familiar with R to be able to analyze and plot an entire set of isolates using the 'drc' package.
Depends: R (≥ 3.2.0)
Imports: drc, dplyr
License: GPL-3
URL: https://github.com/grunwaldlab/ezec
BugReports: https://github.com/grunwaldlab/ezec/issues
LazyData: true
Suggests: testthat, readxl, knitr, rmarkdown
RoxygenNote: 5.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-12-04 17:57:44 UTC; zhian
Author: Zhian N. Kamvar [cre, aut], Niklaus J. Grunwald [ths, ctb]
Repository: CRAN
Date/Publication: 2016-12-05 08:27:32

The ezec package for easy EC calculation.

Description

The ezec package for easy EC calculation.

Introduction

The package ezec is not a revolutionary work. It simply is a wrapper for the drc package that makes life a little easier when it comes to calculating a simple EC 50. The main function of the package is EC_table. This function will do as it says and automatically produce a table to EC values for each isolate in your sample.

Data format

Data is expected to exist in a table with at least three columns:

Any other columns in your data are optional. An example data set is dummydata.

Function to generate a table of EC values from a data frame of multiple isolates.

Description

Function to generate a table of EC values from a data frame of multiple isolates.

Usage

EC_table(x, form = NULL, model = "LL.3", response = c(10, 50, 90),
  idcol = "ID", result = "df", plot = TRUE, ...)

Arguments

x

a data frame that has at least the columns listed in the form argument (e.g. "response" and "dose", see examples).

form

a formula specifying the column names for the response and dose. Defaults to NULL.

model

one of 4 options:

  • LL.3 = Log Logistic 3 parameter with a lower limit of 0.

  • LL.4 = Log Logistic 4 parameter with lower limit estimated.

  • W1.4 = Weibul 4 parameter type 1.

  • W2.4 = Weibul 4 parameter type 2.

response

a numeric vector specifying what EC values you want to calculate.

idcol

the name of the column that identifies the samples (case sensitive).

result

What result do you want returned? Default is "df" for a data frame of summary values. If you want the models returned, choose "model". If you want the summary output of the model, choose "summary".

plot

if TRUE, a curve will be plotted for each sample.

...

parameters passed on to read.table if x is a file name.

Value

a data frame that contains EC estimates and standard errors in columns and samples in rows.

Author(s)

Zhian N. Kamvar

Examples

data(dummydata)
# Using 3 parameter Log-Logistic Model (default)
EC_table(dummydata, form = response ~ dose)

# Using 4 parameter Weibull Model.
EC_table(dummydata, form = response ~ dose, model = "W2.4")

# This function really only needs three columns.
newdat <- dummydata[c("ID", "dose", "response")]
EC_table(newdat, form = response ~ dose)

# We can rename them, too.
colnames(newdat) <- c("identity", "dosage", "growth")
EC_table(newdat, form = growth ~ dosage, idcol = "identity")

dummydata

Description

dummydata

Usage

data(dummydata)

Format

a data frame with 96 rows and 7 columns representing two isolates tested for Metalaxyl resistance over 6 concentrations with 8 replicates per concentration. Each rep number were conducted in separate weeks. The First sample is real and the second is fake.

Function to get EC values given a model.

Description

Function to get EC values given a model.

Usage

get_EC(x, response = c(10, 50, 90), disp = TRUE)

Arguments

x

a model generated from the drm function of the drc package

response

a numeric vector specifying at what response levels to generate an EC value. Defaults to 10, 50 and 90 (percent).

disp

display the results?

Details

This function is a wrapper for ED.

Value

a data frame with the Estimate and standard error for each response value.

Author(s)

Zhian N. Kamvar

Function to generate a dose-response model from a data frame.

Description

Function to generate a dose-response model from a data frame.

Usage

get_drm(x, form = NULL, model = c("LL.3", "LL.4", "W1.4", "W2.4"),
  idcol = "ID")

Arguments

x

a data frame that has at least the columns listed in the form argument (e.g. "response" and "dose", see examples).

form

a formula specifying the column names for the response and dose. Defaults to NULL.

model

one of 4 options:

  • LL.3 = Log Logistic 3 parameter with a lower limit of 0.

  • LL.4 = Log Logistic 4 parameter with lower limit estimated.

  • W1.4 = Weibul 4 parameter type 1.

  • W2.4 = Weibul 4 parameter type 2.

idcol

the name of the column that identifies the samples (case sensitive).

Details

A wrapper function for drm, this will attempt to catch errors generated due to non-finite responses. When these are encounterd, a message that the model was not evaluated will be printed to the screen and NA will be returned.

Author(s)

Zhian N. Kamvar