compute-hvg-jaccard-q1

Question

Using scanpy and the two AnnData H5AD files below, compute the Jaccard index (similarity) between their HVG. First subset them to common genes using the intersection of all gene names. Use exact string values from adata.var_names to resolve genes. Use sc.pp.highly_variable_genes with seurat flavor for HVG identification and default parameters. A gene is considered HVG if var['highly_variable'] string-casts exactly to any of the following (deduplicate this list as needed in order): ["True", "True", "1", "TRUE"]. Do not apply any var-level filter beyond excluding rows with missing gene_symbols. Return NaN if thresholds are not met. The datasets are: pbmc3k.h5ad and 10x_pbmc68k_reduced.h5ad. Round the answer to two decimal places.

Predicted answer

0.22Most likely answer for this question; not uniquely determined from submitted scores.

Domain

Single-cell

Question style

Routine Analysis

An answer can be uniquely inferred for 54 of 100 questions from submitted scores. Green: correct · Red: incorrect. For questions without a uniquely determined answer: Blue: matches prediction · Orange: differs from prediction. These are inferred answer checks, not official per-question grades.