Creates a matrix with aggregated expression values for arbitrary groups of genes
aggregate_gene_expression(
cds,
gene_group_df = NULL,
cell_group_df = NULL,
norm_method = c("log", "binary", "size_only"),
pseudocount = 1,
scale_agg_values = TRUE,
max_agg_value = 3,
min_agg_value = -3,
exclude.na = TRUE
)The cell_data_set on which this function operates
A dataframe in which the first column contains gene ids or short gene names and the second contains groups. If NULL, genes are not grouped.
A dataframe in which the first column contains cell ids and the second contains groups. If NULL, cells are not grouped.
How to transform gene expression values before aggregating them. If "log", a pseudocount is added. If "size_only", values are divided by cell size factors prior to aggregation.
Value to add to expression prior to log transformation and aggregation.
Whether to center and scale aggregated groups of genes.
If scale_agg_values is TRUE, the maximum value the resulting Z scores can take. Higher values are capped at this threshold.
If scale_agg_values is TRUE, the minimum value the resulting Z scores can take. Lower values are capped at this threshold.
Logical indicating whether or not to exclude NA values from the aggregated matrix.
A matrix of dimension NxM, where N is the number of gene groups and M is the number of cell groups.