Tools#
The DRVI tools module provides utilities for analyzing and interpreting latent representations.
Overview#
The tools module is organized into two main categories:
Latent Dimension Analysis: Functions for analyzing and characterizing latent dimensions
Interpretability Tools: Functions for understanding how latent dimensions affect gene expression
Latent Dimension Analysis#
Set the latent dimension statistics of a DRVI embedding into var of an AnnData. |
set_latent_dimension_stats#
Analyzes and characterizes latent dimensions by computing various statistics.
Calculates basic statistics and reconstruction effect for each dimension
Identifies vanished dimensions that contribute little to the model
Provides ranking and ordering of dimensions by importance
Essential for understanding
Use Cases:
Identify and filter out non-informative dimensions
Rank dimensions for downstream analysis and visualization
Interpretability Tools#
Perform latent space traversal and enrich with metadata. |
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Calculate differential variables based on a combination of max_possible and min_possible effects. |
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Get split effects by performing latent traversal and differential analysis. |
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Create an iterator of top differential variables per latent dimension. |
traverse_latent#
Performs systematic traversals through latent dimensions to understand their effects on gene expression.
Systematically varies each latent dimension while keeping others fixed
Generates synthetic data points across the latent space
Enables analysis of how individual dimensions affect gene expression
Should be used with the next function
Use Cases:
Understand how each latent dimension affects gene expression
calculate_differential_vars#
Identifies genes that are differentially affected by latent dimension changes (traverses).
Computes various differential effect metrics (max_possible, min_possible, combined_score)
Identifies genes most relevant to each latent dimension
Use Cases:
Identify genes related to specific biological processes
Quantify the strength of gene-latent dimension relationships
Generate gene lists for downstream biological analysis
get_split_effects#
This function is simply the combination of traverse_latent and calculate_differential_vars.
iterate_on_top_differential_vars#
Iterative over top relevant genes.
Use Cases:
Can be used to construct a for loop over top relevant dimensions.
It can be used along other tools for biological interpretations of latent dimensions