Find Gini Markers¶

findMarkers()

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

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¶

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

Value¶

A data.table with marker genes.

Details¶

Detection of marker genes using the Gini Coefficient is based on the following steps/principles per gene:

calculate average expression per cluster
calculate detection fraction per cluster
calculate gini-coefficient for av. expression values over all clusters
calculate gini-coefficient for detection fractions over all clusters
convert gini-scores to rank scores
for each gene create combined score = detection rank x expression rank x expr gini-coefficient x detection gini-coefficient
for each gene sort on expression and detection rank and combined score

As a results “top gini” genes are genes that are very selectively 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 specify cluster IDs to the parameters group_1 and group_2.

Examples¶

data(mini_giotto_single_cell)

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