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v2_0.md

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Overview

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 from choose_clustering.
  • modalities: an array of names of all available modalities. This is typically determined from the inputs step.
  • num_features: an array of length equal to modalities, containing the number of features present in each modality. This is typically determined from the inputs step.

Parameters

parameters should be empty.

Results

results should contain per_cluster, a group containing the marker results for each cluster. Each child of per_cluster is named after a cluster index from 0 to num_clusters - 1, and is itself a group containing children named according to modalities. Each modality-specific child is yet another group containing the statistics for that modality:

  • means: a float dataset of length equal to the number of features for this modality (as determined from num_features), containing the mean expression of each feature in the current cluster.
  • detected: a float dataset of length equal to the number of features, containing the proportion of cells with detected expression of each feature 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 to the number of features, containing the minimum log-fold change across all pairwise comparisons for each feature.
    • mean: a float dataset of length equal to the number of features, containing the mean log-fold change across all pairwise comparisons for each feature.
    • min_rank: a float dataset of length equal to the number of features, containing the minimum rank of the log-fold changes across all pairwise comparisons for each feature.
  • delta_detected: same as lfc, but for the delta-detected (i.e., difference in the percentage of detected expression).
  • cohen: same as lfc, but for Cohen's d.
  • auc: same as lfc, but for the AUCs.

History

Updated in version 2.0, with the following changes from the previous version:

  • Support markers for multiple modalities.