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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
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.