model_response: Generates a model response

In ropensci/DoOR.functions: Integrating Heterogeneous Odorant Response Data into a Common Response Model: A DoOR to the Complete Olfactome

Generates a model response

Description

Runs the DoOR algorithm, that merges all measurements for one receptor into a common response model.

Usage

model_response(da, select.MDValue = door_default_values("select.MDValue"),
  overlapValues = door_default_values("overlapValues"),
  responseRange = door_default_values("door_response_range"),
  weightGlobNorm = door_default_values("door_global_normalization_weights"),
  glob.normalization = door_default_values("glob.normalization"),
  plot = door_default_values("plot"))

Arguments

da	data frame, a selected receptor containing measured responses from studies.
select.MDValue	numeric, threshold on the MD for rejecting a fit.
overlapValues	numeric, a criterion using to refuse a data set that has not enough overlap value.
responseRange	data frame, contains response ranges for all studies.
weightGlobNorm	data frame, a binary data matrix, 1 indicates given odor has been measured in given study, NA indicates NOT.
glob.normalization	logical, default is TRUE, performs a global normalization for the model response. Otherwise (FALSE) response values will be given in value from 0 to 1.
plot	logical, If FALSE, plotting is suppressed. Default is FALSE.

Details

Merging a data is processed by following:

1. Normalize all response data in value [0,1].

2. Compute the correlation between studies and selected the best pair using select_model.

3. Merge the first pair using function project_points.

4. Add other datasets if the correlation between the growing model response and the new dataset is below the correlation threshold (select.MDValue). Datasets excluded based on this criterion will be appended in a separate list.

Author(s)

Shouwen Ma <[e-mail]>

Examples

# load data
library(DoOR.data)
data(Or35a)
data(door_global_normalization_weights)
data(door_response_range)

# merge all existing data sets for Or35a into a consensus model response
model_response_Or35a <- model_response(Or35a, plot = TRUE)

ropensci/DoOR.functions documentation built on Feb. 22, 2024, 9:44 a.m.