get_condition_biased_comigrations: get_condition_biased_comigrations

In XINA: Multiplexes Isobaric Mass Tagged-based Kinetics Data for Network Analysis

Description

get comigrations that at least one biased cluster is involved in. Biased clusters are defined by

Usage

get_condition_biased_comigrations(clustering_result, count_table = NULL,
  selected_conditions, condition_composition, threshold_percent = 50,
  color_for_null = "gray", color_for_highly_matched = "red4",
  cex = 0.7, alpha = 0.3)

Arguments

clustering_result	A list containing XINA clustering results. See xina_clustering
count_table	A data frame generated by using count. If count_table is NULL (by default), XINA will consider all the comigrations.
selected_conditions	A vector of condition names used in XINA clustering results. The number of selected conditions should be at least two.
condition_composition	The resulting data frame of 'plot_condition_compositions'. See plot_condition_compositions.
threshold_percent	Default is 50. The percentage threshold for finding condition-biased clusters
color_for_null	A color for non-condition-biased comigrations. Default is 'gray'
color_for_highly_matched	A color for comigrations that are involved with more than two condition-biased clusters. Default is 'red4'
cex	Size of cluster number on block axis. Default if 0.7. See alluvial.
alpha	Transparency of alluvia colors. Default is 0.3. See alluvial.

Value

An alluvial plot displaying comigrations and the data frame containing condition-biased comigrations.

Examples

# load XINA example data
data(xina_example)

# get a vector of experimental conditions analyzed in the clustering results
conditions <- as.vector(example_clusters$condition)

# get condition composition information
condition_composition <- plot_condition_compositions(example_clusters)

comigrations_size10 <- alluvial_enriched(example_clusters, conditions, comigration_size=10)
# Finding condition-biased comigrations by 50% threshold
condition_biased_comigrations <-
get_condition_biased_comigrations(clustering_result=example_clusters,
count_table=comigrations_size10, selected_conditions=conditions,
condition_composition=condition_composition)

# Finding condition-biased comigrations by 70% threshold
condition_biased_comigrations <-
get_condition_biased_comigrations(clustering_result=example_clusters,
count_table=comigrations_size10, selected_conditions=conditions,
condition_composition=condition_composition,
threshold_percent=70)

XINA documentation built on Nov. 8, 2020, 5:32 p.m.