Description Usage Arguments Value Examples
View source: R/coregulstions.R
get comigrations that at least one biased cluster is involved in. Biased clusters are defined by
1 2 3 4 | 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)
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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. |
An alluvial plot displaying comigrations and the data frame containing condition-biased comigrations.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | # 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)
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