ARI Value for DLPFC and HBC Dataset: STESH Clustering Performance Metrics

STESH clustering method performance metrics for spatial transcriptomics data. The dataset contains adjusted Rand index, normalized mutual information, and Fowlkes-Mallows index scores for the DLPFC and HBC tissue types. Author Huihui Zhang published the 11.0 KB Excel file on figshare in June 2026.

Use Cases

• Benchmarking spatial transcriptomics clustering methods based on the reported ARI, NMI, and FMI scores.
• Validating the performance of the STESH method on the DLPFC and HBC tissue types mentioned in the description.
• Comparing multi-view graph convolutional network approaches for integrating gene expression, spatial location, and histology.

Strengths

• Dataset is small at 11.0 KB, enabling quick download and inspection.
• Performance is quantified using three standard clustering metrics: adjusted Rand index, normalized mutual information, and Fowlkes-Mallows index.
• Published under a permissive CC-BY-4.0 license.

Limitations

• The dataset's scale is limited to 11.0 KB, suggesting a small number of summary metric values rather than raw data.
• Row count and column-level documentation are unknown, requiring manual inspection after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, author Huihui Zhang.

Collection Method

Likely contains aggregated evaluation metrics from the STESH clustering method applied to spatial transcriptomics data.

Freshness

Last updated 2026-06-01 17:40:30; freshness should be verified.