Integrated analysis of multimodal single-cell data

Abstract The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially…

• BA
  Bill and Melinda Gates Foundation

  Award: OPP1113682
• CZ
  Chan Zuckerberg Initiative

  Awards: HCA-A-1704-01895, EOSS-0000000082, U19AI128914
• NI
  National Institutes of Health

  Awards: RM1HG011014, AI068618, DP2HG009623-01, RM1HG011014-01, R21HG009748-03, U19AI128914, UM1 AI068618