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Description

Transcriptomic Scoring for Human Skeletal Muscle Health.

Calculate MyoScore, a genetically informed muscle health score, from bulk RNA sequencing (RNA-seq) raw count data. MyoScore integrates results from genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) across 28 muscle-related phenotypes to quantify muscle health along five dimensions (Strength, Mass, LeanMuscle, Youth, Resilience), each scored from 0 to 100. The package provides preprocessing via counts per million (CPM) normalization, dimension-level and composite scoring, and visualization utilities including radar charts and grouped boxplots. For more information, see <https://github.com/Hirriririir/MyoScore>.

MyoScore

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.

Installation

# Install from GitHub
devtools::install_github("Hirriririir/MyoScore")

Quick Start

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

Five Dimensions

DimensionWeightGWAS Basis
Strength25.2%Grip strength, walking pace
Mass17.7%Fat-free mass (whole body, limbs)
LeanMuscle24.3%Thigh fat infiltration MRI
Youth24.2%Telomere length
Resilience8.7%Myopathy diagnosis, CK levels

Higher score = healthier muscle (0-100 scale)

Visualization

# Radar chart (requires fmsb)
myoscore_plot_radar(scores, groups = metadata$condition)

# Grouped boxplot (requires ggplot2)
myoscore_plot_boxplot(scores, groups = metadata$condition)

Input Requirements

  • Raw count matrix (genes x samples), not TPM/FPKM
  • Gene Symbols as row names
  • At least 2 samples (recommend >= 20)

Citation

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

License

MIT.

Metadata

Version

1.0.1

License

Unknown

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