A genetically-informed transcriptomic scoring system for quantifying human skeletal muscle health
MyoScore quantifies skeletal muscle health across five genetically-driven dimensions based on GWAS-TWAS integration of 28 muscle-related phenotypes.
# Install from GitHub
devtools::install_github("Hirriririir/MyoScore")library(MyoScore)
# Calculate MyoScore from raw count matrix
scores <- myoscore_score("path/to/raw_counts.csv")
# Or from an R matrix
scores <- myoscore_score(count_matrix)
# View results
head(scores)
#> Strength_score Mass_score LeanMuscle_score Youth_score Resilience_score MyoScore
#> S1 72.3 65.1 80.2 55.8 68.4 69.2
#> S2 45.1 38.7 42.3 61.2 35.6 44.1| Dimension | Weight | GWAS Basis |
|---|---|---|
| Strength | 25.2% | Grip strength, walking pace |
| Mass | 17.7% | Fat-free mass (whole body, limbs) |
| LeanMuscle | 24.3% | Thigh fat infiltration MRI |
| Youth | 24.2% | Telomere length |
| Resilience | 8.7% | Myopathy diagnosis, CK levels |
Higher score = healthier muscle (0-100 scale)
# Radar chart (requires fmsb)
myoscore_plot_radar(scores, groups = metadata$condition)
# Grouped boxplot (requires ggplot2)
myoscore_plot_boxplot(scores, groups = metadata$condition)Revealing myopathy spectrum: integrating transcriptional and clinical features of human skeletal muscles with varying health conditions. Communications Biology, 2024. DOI: 10.1038/s42003-024-06096-7
MIT