reorder_clusters_stepdown {seqsetvis} | R Documentation |
Attempts to reorder clusters so that rows with highest signal on the left relative to the right appear at the top. Signal should have a roughly diagonal pattern in a "stepdown" pattern.
reorder_clusters_stepdown( clust_dt, row_ = "id", column_ = "x", fill_ = "y", facet_ = "sample", cluster_ = "cluster_id", reapply_cluster_names = TRUE, step_by_column = TRUE, step_by_facet = FALSE )
clust_dt |
data.table output from |
row_ |
variable name mapped to row, likely id or gene name for ngs data. Default is "id" and works with ssvFetch* output. |
column_ |
varaible mapped to column, likely bp position for ngs data. Default is "x" and works with ssvFetch* output. |
fill_ |
numeric variable to map to fill. Default is "y" and works with ssvFetch* output. |
facet_ |
variable name to facet horizontally by. Default is "sample" and works with ssvFetch* output. Set to "" if data is not facetted. |
cluster_ |
variable name to use for cluster info. Default is "cluster_id". |
reapply_cluster_names |
If TRUE, clusters will be renamed according to new order instead of their original names. Default is TRUE. |
step_by_column |
If TRUE, column is considered for left-right cluster balance. Default is TRUE. |
step_by_facet |
If TRUE, facet is considered for left-right cluster balance. Default is FALSE. |
This can be down by column (step_by_column = TRUE) which averages across facets. By facet (step_by_column = FALSE, step_by_facet = TRUE) which averages all columns per facet. Or both column and facet (step_by_column = TRUE, step_by_facet = TRUE), which does no averaging so it looks at the full matrix as plotted.
data.table as output from ssvSignalClustering
clust_dt = ssvSignalClustering(CTCF_in_10a_profiles_dt, nclust = 10) new_dt = reorder_clusters_stepdown(clust_dt) cowplot::plot_grid( ssvSignalHeatmap(clust_dt), ssvSignalHeatmap(new_dt) )