Compute deconvolution subgroups

Groups the features of one cell type by complete-linkage hierarchical clustering on their correlations: features end up in the same subgroup only if every pair of them correlates at least thres_corr (non-significant correlations, p >= 0.05, count as 0). Each subgroup is replaced by the row median of its members. The result does not depend on the column order.

Usage

compute_subgroups(
  deconvolution,
  thres_corr,
  corr_type,
  file_name,
  batch = NULL
)

Arguments

deconvolution

A matrix with the deconvolution features of one cell type (samples as rows)

thres_corr

A numeric value with the minimum correlation allowed to group cell deconvolution features

corr_type

Correlation type whether "spearman" or "pearson".

file_name

Cell type name, used as prefix of the subgroup names (<file_name>_Subgroup.<i>)

batch

Optional batch labels, one per sample in the same order as the rows. A factor or character is treated as categorical: correlations become partial correlations controlling for one indicator column per batch. A numeric vector is used as a single linear covariate.

Value

A list containing

• A data frame with the final features: the subgroup medians plus the features that were not grouped

• The subgroups composition: a named list with the members of every subgroup