Analyzing epigenetic modifications at sample-specific CpG loci in long-read data using a likelihood-based framework in bsseq.

A likelihood-based, read-level framework in bsseq identifies reference and non-reference sample-specific CpG loci with high precision and sensitivity in Nanopore and PacBio single-molecule long-read data.

• Why it matters: Sample-specific CpG loci are difficult to pinpoint for epigenetic analysis, and missing loci can bias modification-level estimates and limit the number of analyzable sites.
• What they did: The method uses a read-based likelihood framework to filter and identify CpG loci in long-read sequencing from Nanopore and PacBio, implemented in the R package bsseq.
• The result: Including all sample-specific CpG loci increases analyzable loci and reduces bias in modification level estimates, enabling more accurate epigenetic modification analyses.

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