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Single cell and spatial sequencing

Single cell genomics approaches have proven to be a powerful tool to distinguish cell types and understand biology at the resolution of the fundamental unit of life, the cell. After an initial stage of exploration and discovery, single cell genomics is now entering a stage of massive scale up – experiments with more cells, more analytes, and more perturbations.

The UG 100™ is an ideal tool to help facilitate the scale up of single cell and spatial genomics.

  • Affordable single cell RNA-seq
  • 200-300K cells per run (20-25K reads per cell)
  • Tools available to convert output to paired end reads
  • Sequencing output compatible with downstream processing tools (CellRangerTM, PIPseekerTM, etc)

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Results comparable to other sequencing technologies

Single cell libraries can be easily converted for sequencing on the UG 100™ platform. Downstream analyses show comparable results regardless of the sequencing platform that was used.

Read our single cell app note


Simmons, S.K., Lithwick-Yanai, G., Adiconis, X. et al. Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing. Nat Biotechnol 41, 204–211 (2023). https://doi.org/10.1038/s41587-022-01452-6

Tested on leading single cell workflows

Scale your single cell experiments with a multitude of leading single cell companies' library prep workflows including:

  • 10x Genomics Chromium Single Cell Gene Expression (3')
  • 10x Genomics Chromium Single Cell Immunoprofiling (5')
  • 10x Genomics Chromium Single Cell Gene Expression Flex
  • Parse Biosciences
  • Fluent Biosciences

Explore our single cell data and analysis


Scale Perturb-Seq assays with >1M cells

Large scale single cell Perturb-Seq assays open new avenues for researches to study complex biological system. Large Pertub-Seq datasets in combination with new AI methods will open a new era for drug discovery and understanding of complex systems.

Read our collaborator's publication in Cell


Replogle JM, Saunders RA, Pogson AN, Hussmann JA, Lenail A, Guna A, Mascibroda L, Wagner EJ, Adelman K, Lithwick-Yanai G, Iremadze N, Oberstrass F, Lipson D, Bonnar JL, Jost M, Norman TM, Weissman JS. Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell. 2022 Jul 7;185(14):2559-2575.e28. doi: 10.1016/j.cell.2022.05.013. Epub 2022 Jun 9. PMID: 35688146; PMCID: PMC9380471.

Resolve and scale your spatial transcriptomic studies to new heights

New methods that read spatial location using sequencing achieve sub cellular level

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Learn how the Satija lab used scalable single-cell perturbation screens to reconstruct molecular pathway signatures.

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Analysis Pipelines

Learn how to analyze 10x 3' scRNA-seq data from the UG 100™ system using our analysis pipeline

Run single cell analysis

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