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BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies.

Wanding ZhouBenjamin K JohnsonJacob MorrisonIan BeddowsJames EapenEfrat KatsmanAyush SemwalWalid Abi HabibLyong HeoPeter W LairdBenjamin P BermanTimothy J TricheHui Shen
Published in: Nucleic acids research (2024)
Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.
Keyphrases
  • single cell
  • dna methylation
  • genome wide
  • rna seq
  • copy number
  • high throughput
  • gene expression
  • single molecule
  • electronic health record
  • healthcare
  • high resolution
  • data analysis
  • artificial intelligence