findGiniMarkers

findGiniMarkers

Description

Identify marker genes for selected clusters based on gini detection and expression scores.

Usage

findGiniMarkers(
  gobject,
  expression_values = c("normalized", "scaled", "custom"),
  cluster_column,
  subset_clusters = NULL,
  group_1 = NULL,
  group_2 = NULL,
  min_expr_gini_score = 0.2,
  min_det_gini_score = 0.2,
  detection_threshold = 0,
  rank_score = 1,
  min_genes = 5
)

Arguments

Argument	Description
gobject	giotto object
expression_values	gene expression values to use
cluster_column	clusters to use
subset_clusters	selection of clusters to compare
group_1	group 1 cluster IDs from cluster_column for pairwise comparison
group_2	group 2 cluster IDs from cluster_column for pairwise comparison
min_expr_gini_score	filter on minimum gini coefficient for expression
min_det_gini_score	filter on minimum gini coefficient for detection
detection_threshold	detection threshold for gene expression
rank_score	rank scores for both detection and expression to include
min_genes	minimum number of top genes to return

Details

Detection of marker genes using the https://en.wikipedia.org/wiki/Gini_coefficient gini

coefficient is based on the following steps/principles per gene:

• 1. calculate average expression per cluster

• 1. calculate detection fraction per cluster

• 1. calculate gini-coefficient for av. expression values over all clusters

• 1. calculate gini-coefficient for detection fractions over all clusters

• 1. convert gini-scores to rank scores

• 1. for each gene create combined score = detection rank x expression rank x expr gini-coefficient x detection gini-coefficient

• 1. for each gene sort on expression and detection rank and combined score

  As a results “top gini” genes are genes that are very selectivily expressed in a specific cluster, however not always expressed in all cells of that cluster. In other words highly specific, but not necessarily sensitive at the single-cell level.

  To perform differential expression between cluster groups you need to specificy cluster IDs to the parameters group_1 and group_2 .

Value

data.table with marker genes

Examples

data(mini_giotto_single_cell)

gini_markers = findGiniMarkers(gobject = mini_giotto_single_cell,
cluster_column = 'leiden_clus',
group_1 = 1,
group_2 = 2)