To complement and inform the analysis of scRNA-Seq datasets, we create methods to simultaneously profile additional cellular characteristics of interest (e.g. genome, epigenome, or proteome), independently, or in combination with, scRNA-Seq. For a given technique or system, we ask what additional information would help us better interpret our scRNA-Seq results and develop methods to collect these data. These novel methods often map ancillary information into a DNA-based readout that can be coanalyzed with cellular mRNA or developing/applying microdevices. Recently, we have developed a method for integrated mRNA and protein detection that leverages proximity extension assays (Genshaft et al. 2016). To extract the information content from these novel datasets more effectively, we also formulate new computational methods and analyses.