. Author manuscript; available in PMC: 2024 Apr 1.

Published in final edited form as: J Immunol. 2023 Apr 1;210(7):859–868. doi: 10.4049/jimmunol.2200660

Table 1:

Multiomics approaches for T cell and TME profiling in PDAC

Technology	Data output	Computational analytical tools
scRNA-seq with matched TCR-seq (10X Genomics, SMART-seq^76,127)	• Phenotype via transcriptome • Paired α/β TCR sequence	RNA^* • Seurat^27–29 • monocle^128–130 • Cumulus¹³¹ • scanpy²⁵ TCR • scRepertoire²⁶ • immunarch³⁰ • scirpy²⁴ • Immcantation portal^132,133
CITE-seq^31,32	• Phenotype via transcriptome and DNA-barcoded surface antibodies • Compatible with multiplexing (i.e. TCR-seq, other 10X Genomics feature barcodes)	• Seurat^27–29 • CITE-seq-Count¹³⁴ • Cumulus¹³¹
DNA-barcoded pMHC multimers (10X Genomics feature-barcode technology, tetTCR-seq^35,135)	• Phenotype via transcriptome and DNA-barcoded surface antibodies • Compatible with multiplexing (i.e. TCR-seq, other 10X Genomics feature barcodes)	• Seurat^27–29 • Cumulus¹³¹
Spatial transcriptomics (Slide-seq⁸³, 10X Genomics Visium and Xenium In Situ, Nanostring DSP⁸⁵ and CosMx, MERFISH¹³⁶)	• Spatially resolved phenotype via RNA expression • α/β TCR sequences^54,137	• Seurat^27–29 • Cumulus¹³¹ • Giotto¹³⁸ • squidpy¹³⁹ • spatialExperiment¹⁴⁰ • spatialLIBD¹⁴¹ • spatialDE¹⁴²

DSP: Digital Spatial Profiling, sDAS: spatial Data Analysis Service

For up-to-date single-cell analytical tools: https://www.scrna-tools.org¹⁴³ Please note that this table is not exhaustive, but rather emphasizes a subset of the many technologies and software available.