model_response_seq: model_response_seq

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

model_response_seq

Description

generates a model response and merge data in given sequence

Usage

model_response_seq(data, SEQ,
  overlapValues = door_default_values("overlapValues"),
  select.MDValue = door_default_values("select.MDValue"), strict = TRUE,
  plot = FALSE)

Arguments

data	data frame, odorant response data, e.g. Or22a.
SEQ	character vector, containing the names of studies indicating given sequence for merging data.
overlapValues	minimum overlap between studies to perfom a merge
select.MDValue	the minimum mean distance between studies to perfom a merge
strict	logical, if TRUE merging a permutation will be stopped once a single merge has a mean distance above select.MDValue
plot	logical

Details

# model_response_seq.R: #################

# merges studies in a given sequence (determined by the user or by exhaustive enumeration and choosing the optimal sequence)

# input parameters: ####################

# data : data frame, odorant response data for a given receptor, e.g. Or22a # SEQ : character vector, contains the names of studies that measured this receptor in a specific order (the merging sequence)

# output is a numeric vector: response values

Author(s)

Shouwen Ma <[e-mail]>

Examples

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

# specify a sequence of merging
SEQ <- c("Hallem.2006.EN","Kreher.2008.EN","Hallem.2006.EN")

# perform the merging
selected_merg <- model_response_seq(Or35a, SEQ = SEQ, plot = TRUE)

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