BMC Bioinformatics (Feb 2024)

Torch-eCpG: a fast and scalable eQTM mapper for thousands of molecular phenotypes with graphical processing units

  • Kord M. Kober,
  • Liam Berger,
  • Ritu Roy,
  • Adam Olshen

DOI
https://doi.org/10.1186/s12859-024-05670-4
Journal volume & issue
Vol. 25, no. 1
pp. 1 – 9

Abstract

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Abstract Background Gene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime. Results We demonstrate the analyses using the tool are reproducible, up to 18 × faster using the GPU, and scale linearly with increasing methylation loci. Conclusions Torch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg .

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