We expect a marker_detection HDF5 group at the root of the file, containing marker statistics for each cluster.
The group itself contains the parameters and results subgroups.
Definitions:
num_clusters: number of clusters in the analysis. This is typically determined fromchoose_clustering.num_genes: number of genes in the analysis. This is typically determined from theinputsstep.
parameters should be empty.
results should contain:
clusters: a group representing an array of length equal to the number of clusters. Each child is another group that is named by the cluster index from 0 tonum_clusters - 1, containing the marker details for that cluster. Each child group contains:means: a float dataset of length equal tonum_genes, containing the mean expression of each gene in the current cluster.detected: a float dataset of length equal tonum_genes, containing the proportion of cells with detected expression of each gene in the current cluster.lfc: an group containing statistics for the log-fold changes from all pairwise comparisons involving the current cluster. This contains:min: a float dataset of length equal tonum_genes, containing the minimum log-fold change across all pairwise comparisons for each gene.mean: a float dataset of length equal tonum_genes, containing the mean log-fold change across all pairwise comparisons for each gene.min_rank: a float dataset of length equal tonum_genes, containing the minimum rank of the log-fold changes across all pairwise comparisons for each gene.
delta_detected: same aslfc, but for the delta-detected (i.e., difference in the percentage of detected expression).cohen: same aslfc, but for Cohen's d.auc: same aslfc, but for the AUCs.
Added in version 1.0.