42 cohorts from 26 public datasets provide a multi-model transcriptomic atlas of skeletal muscle atrophy. This dataset, created by Zhaolu Wang, integrates data from seven canonical mouse models including aging, cancer cachexia, and denervation. It was last updated on April 15, 2026.
Use Cases
- Identify conserved transcriptomic signatures of muscle atrophy across seven mouse models.
- Compare model-specific gene expression patterns between conditions like cancer cachexia and hindlimb unloading.
- Train predictive models for muscle atrophy states based on integrated transcriptomic profiles.
- Validate findings from one atrophy model against a compendium of other experimental conditions.
Strengths
- Integrates data from 42 cohorts across 26 publicly available datasets.
- Covers seven distinct mouse models of skeletal muscle atrophy.
- Released under a permissive CC-BY-4.0 license.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The 88.7 MB size suggests a relatively small dataset for transcriptomics.
Provenance
- Source
- figshare, accompanying a research article by Zhaolu Wang.
- Collection Method
- Integrated collection from 26 publicly available transcriptomic datasets.
- Time Range
- null
- Freshness
- Last updated 2026-04-15 00:10:09; freshness should be verified.
- Geography
- null