Torch-eCpG

Torch-eCpG performs expression quantitative trait methylation (eQTM) mapping to identify expression-associated CpG (eCpG) loci and characterize cis, distal, and trans DNA methylation–gene expression associations.

Key Features:

• eQTM mapping: Implements expression quantitative trait methylation analyses to detect CpG loci associated with gene expression.
• eCpG identification: Identifies expression-associated CpG (eCpG) loci across genomic regions including cis, distal, and trans.
• GPU acceleration: Leverages graphical processing units (GPUs) for computational performance improvements.
• CPU comparison: Demonstrates up to 18× speedup relative to traditional CPU-based methods.
• Linear scaling: Exhibits linear scaling behavior with increasing numbers of methylation loci.
• High-throughput capacity: Designed to handle the extensive number of comparisons required for analyses involving thousands of molecular phenotypes.

Scientific Applications:

• Regulatory methylation studies: Mapping eQTMs to investigate the regulatory influence of DNA methylation on gene expression.
• Cis, distal, and trans association analysis: Characterizing methylation–expression associations across cis, distal, and trans genomic contexts.
• Large-scale molecular phenotype studies: Enabling analyses that involve thousands of molecular phenotypes and extensive pairwise comparisons.
• Comparative performance evaluation: Providing a high-performance platform for benchmarking methylation–expression association methods against CPU-based approaches.

Methodology:

GPU-accelerated implementation with optimizations for linear scaling across methylation loci and benchmarking against CPU implementations showing up to 18× reduced runtime.