scMD facilitates cell type deconvolution using single-cell DNA methylation references

The proliferation of single-cell RNA-sequencing data has led to the widespread use of cellular deconvolution, aiding the extraction of cell-type-specific information from extensive bulk data. However, those advances have been mostly limited to transcriptomic data. With recent developments in single-cell DNA methylation (scDNAm), there are emerging opportunities for deconvolving bulk DNAm data, particularly for solid tissues like brain that lack cell-type references. Due to technical limitations, current scDNAm sequences represent a small proportion of the whole genome for each single cell, and those detected regions differ across cells. This makes scDNAm data ultra-high dimensional and ultra-sparse. To deal…

• UO
  University of Pittsburgh

  Award: UL1TR001857
• RU
  Rush University
• NI
  National Institutes of Health

  Awards: R03OD034501, U01AG46152, U01AG61356, R01MH123184, R01AG15819, P30AG10161, UL1TR001857
• CF
  Center for Research Computing, University of Pittsburgh
• NI
  National Institute on Aging

  Awards: UL1TR001857, U01AG61356, R01AG15819, U01AG46152, P30AG10161