MuscleAtlasExplorer
MuscleAtlasExplorer provides access to a curated compendium of human skeletal muscle gene expression data linked to phenotype metadata for comparative and hypothesis-driven analyses.
Key Features:
- Extensive Dataset: Contains a comprehensive collection of gene expression data from human skeletal muscle samples.
- Curated Phenotype Data: Integrates sample-level phenotype metadata including age, sex, body mass index (BMI), and disease status.
- Data Visualization Tools: Implements visualization functions to explore expression patterns and relationships within the datasets.
- Sample Selection and In-depth Inspection: Enables selection of specific samples for focused examination of particular genes or conditions.
- Integration with External Tools: Provides compatibility with external bioinformatics tools to extend downstream analyses.
Scientific Applications:
- Muscular disease research: Correlates gene expression with disease status to support investigation of genetic contributors to muscle disorders.
- Aging-related muscle studies: Enables analysis of age-associated changes in skeletal muscle gene expression.
- Sex-specific expression analysis: Facilitates comparison of gene expression differences between sexes in muscle tissue.
- Gene function and comparative analyses: Supports hypothesis-driven exploration of gene function within human skeletal muscle using phenotype-linked expression data.
Methodology:
Integration of gene expression datasets with curated phenotype metadata, visualization-based exploration, sample-level selection for inspection, and compatibility with external bioinformatics tools.
Topics
Details
- Tool Type:
- web application
- Added:
- 1/18/2021
- Last Updated:
- 3/2/2021
Operations
Publications
Asplund O, Rung J, Groop L, Prasad B R, Hansson O. MuscleAtlasExplorer: a web service for studying gene expression in human skeletal muscle. Database. 2020;2020. doi:10.1093/database/baaa111. PMID:33338203. PMCID:PMC7747357.
PMID: 33338203
PMCID: PMC7747357
Funding: - Swedish Foundation for Strategic Research: IRC15-0067
- Linnaeus Grant: 349-2006-237
- Vetenskapsrådet: 2009-1039, 2018-02635