Multi-omics single cell analysis is based on simultaneous detection of different types of biological molecules on the same cells.  Common multi-omics techniques include feature barcoding or CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) technologies, which enable parallel assessment of gene and protein expression. Specific bioinformatics tools have been developed to enable scientists to integrate results of multiple assays and learn relative importance of each type (or each biological molecule) in identification of cell types. Partek Flow supports weighted nearest neighbour analysis (1), which can help combine output of two or more assays.

To start, select a PCA data node of one of the assays (e.g. gene expression) and go to Exploratory analysis > Find multimodal neighbours in the toolbox.

1. Hao Y, Hao S, Andersen-Nissen E, et al. Integrated analysis of multimodal single-cell data. Cell. 2021;184(13):3573-3587.e29. doi:10.1016/j.cell.2021.04.048