R: Load list of level 5 multiple-concentration cutoff methods

MC5_Methods {tcpl}

R Documentation

Load list of level 5 multiple-concentration cutoff methods

Description

mc5_mthds returns a list of additional activity cutoff methods to be used during level 5 multiple-concentration processing.

Usage

mc5_mthds(ae)

Arguments

`ae`	Integer of length 1, the assay endpoint id

Details

The functions contained in the list returned by mc5_mthds take aeids (a numeric vector of aeid values) and returns a list of expressions to be executed in the mc5 (not exported) function environment. The functions are described here for reference purposes, The mc5_mthds function is not exported, nor is it intended for use.

All available methods are described in the "Available Methods" section, listed by the cutoff type in ascending order of cutoff value.

Value

A list of functions

Available Methods

The methods are broken down into five categories based on the type of cutoff they assign. Different methods are used to define cutoffs for "bmad" (baseline median absolute value), "fc" (fold change), "log" (\log_{2} or \log_{10}), "pc" (percent of control), and "other" (uncategorized cutoffs).

All methods are applied by aeid.

Although there are method exceptions (notably within the “other” category), only highest calculated cutoff value based on assigned methods will be selected for hitcalling. Therefore, only the largest cutoff method per method type should be assigned.

More information about the level 5 multiple-concentration processing is available in the package vignette, "Data_processing."

BMAD Methods

bmad1: Add a cutoff value of 1 multiplied by baseline median absolute value (bmad). By default, bmad is calculated using test compound wells (wllt = t) for the endpoint.
bmad2: Add a cutoff value of 2 multiplied by the baseline median absolute deviation (bmad). By default, bmad is calculated using test compound wells (wllt = t) for the endpoint.
bmad3: Add a cutoff value of 3 multiplied by the baseline median absolute deviation (bmad) as defined at Level 4.
bmad4: Add a cutoff value of 4 multiplied the baseline median absolute deviation (bmad). By default, bmad is calculated using test compound wells (wllt = t) for the endpoint.
bmad5: Add a cutoff value of 5 multiplied the baseline median absolute deviation (bmad). By default, bmad is calculated using test compound wells (wllt = t) for the endpoint.
bmad6: Add a cutoff value of 6 multiplied by the baseline median absolute deviation (bmad). By default, bmad is calculated using test compound wells (wllt = t) for the endpoint.
bmad10: Add a cutoff value of 10 multiplied by the baseline median absolute deviation (bmad). By default, bmad is calculated using test compound wells (wllt = t) for the endpoint.

Fold Change Methods

fc0.2: Add a cutoff value of 0.2. Typically for zero centered fold change data.
fc0.3: Add a cutoff value of 0.3. Typically for zero centered fold change data.

Log Methods

Log Base 2

neglog2_0.88: Add a cutoff value of -\log_{2}{0.88}.
log2_1.2: Add a cutoff value of \log_{2}{1.2}. Typically for fold change data.
log2_2: Add a cutoff value \log_{2}{2}. Typically for fold change data.

Log Base 10

log10_1.2: Add a cutoff value of \log_{10}{1.2}. Typically for fold change data.
log10_2: Add a cutoff value of \log_{10}{2}. Typically for fold change data.

Percent of Control Methods

pc05: Add a cutoff value of 5. Typically for percent of control data.
pc10: Add a cutoff value of 10. Typically for percent of control data.
pc20: Add a cutoff value of 20. Typically for percent of control data.
pc25: Add a cutoff value of 25. Typically for percent of control data.
pc30: Add a cutoff value of 30. Typically for percent of control data.
pc50: Add a cutoff value of 50. Typically for percent of control data.
pc70: Add a cutoff value of 70. Typically for percent of control data.
pc95: Add a cutoff value of 95. Typically for percent of control data.

Other Methods

maxmed20pct: Add a cutoff value of 20 percent of the maximum of all endpoint maximal average response values (max_med).
coff_2.32: Add a cutoff value of 2.32.
loec.coff: Method not yet updated for tcpl implementation. Identify the lowest observed effective concentration (loec) compared to baseline.

Note

This function is not exported and is not intended to be used by the user.