aggregate_gene_expression: Creates a matrix with aggregated expression values for...

In cole-trapnell-lab/monocle3: Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Description

Creates a matrix with aggregated expression values for arbitrary groups of genes

Usage

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
)

Arguments

cds	The cell_data_set on which this function operates
gene_group_df	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.
cell_group_df	A dataframe in which the first column contains cell ids and the second contains groups. If NULL, cells are not grouped.
norm_method	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.
pseudocount	Value to add to expression prior to log transformation and aggregation.
scale_agg_values	Whether to center and scale aggregated groups of genes.
max_agg_value	If scale_agg_values is TRUE, the maximum value the resulting Z scores can take. Higher values are capped at this threshold.
min_agg_value	If scale_agg_values is TRUE, the minimum value the resulting Z scores can take. Lower values are capped at this threshold.
exclude.na	Logical indicating whether or not to exclude NA values from the aggregated matrix.

Value

A matrix of dimension NxM, where N is the number of gene groups and M is the number of cell groups.

cole-trapnell-lab/monocle3 documentation built on April 8, 2021, 5:54 a.m.