HCA Data Explorer

Cell hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics

Updated October 20, 2021

Despite rapid developments in single cell sequencing technology, sample-specific batch effects, detection of cell doublets, and the cost of generating massive datasets remain outstanding challenges. Here, we introduce cell hashing, where oligo-tagged antibodies against ubiquitously expressed surface proteins are used to uniquely label cells from distinct samples, which can be subsequently pooled. By sequencing these tags alongside the cellular transcriptome, we can assign each cell to its sample of origin, and robustly identify doublets originating from multiple samples. We demonstrate our approach by pooling eight human PBMC samples on a single run of the 10x Chromium system, substantially reducing our per-cell costs for library generation. Cell hashing is inspired by, and complementary to, elegant multiplexing strategies based on genetic variation, which we also leverage to validate our results. We therefore envision that our approach will help to generalize the benefits of single cell multiplexing to diverse samples and experimental designs.

Rahul SatijaNew York Genome Centerrsatija@nygenome.org
Peter SmibertNew York Genome Centerpsmibert@nygenome.org
Rahul Satija (Principal Investigator)1
Peter Smibert (Co-Investigator)1
Marlon Stoeckius (Experimental Scientist)1
Shiwei Zheng (Experimental Scientist)1
1New York Genome Center
William G Sullivan

To reference this project, please use the following link:

https://explore.data.humancellatlas.dev.clevercanary.com/projects/f81efc03-9f56-4354-aabb-6ce819c3d414
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Atlas

None

Analysis Portals

None

Project Label

Multiplexed scRNA-seq with barcoded antibodies

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

blood

Organ Part

Unspecified

Selected Cell Types

peripheral blood mononuclear cell

Disease Status (Specimen)

Unspecified

Disease Status (Donor)

normal

Development Stage

human adult stage

Library Construction Method

CITE-seq

Nucleic Acid Source

single cell

Paired End

false

File Format

2 file formats

Cell Count Estimate

20.0k

Donor Count

8
fastq.gz6 file(s)tar1 file(s)