CellWalker integrates single-cell and bulk data to resolve regulatory elements across cell types in complex tissues

Genome Biol. 2021 Feb 14;22(1):61. doi: 10.1186/s13059-021-02279-1.


Single-cell and bulk genomics assays have complementary strengths and weaknesses, and alone neither strategy can fully capture regulatory elements across the diversity of cells in complex tissues. We present CellWalker, a method that integrates single-cell open chromatin (scATAC-seq) data with gene expression (RNA-seq) and other data types using a network model that simultaneously improves cell labeling in noisy scATAC-seq and annotates cell type-specific regulatory elements in bulk data. We demonstrate CellWalker's robustness to sparse annotations and noise using simulations and combined RNA-seq and ATAC-seq in individual cells. We then apply CellWalker to the developing brain. We identify cells transitioning between transcriptional states, resolve regulatory elements to cell types, and observe that autism and other neurological traits can be mapped to specific cell types through their regulatory elements.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Chromatin Immunoprecipitation Sequencing / methods
  • Computational Biology / methods*
  • Gene Expression Regulation*
  • Genetic Loci
  • Molecular Sequence Annotation
  • Organ Specificity / genetics
  • Regulatory Sequences, Nucleic Acid*
  • Reproducibility of Results
  • Single-Cell Analysis* / methods
  • Software*