Comprehensive Integration of Single-Cell Data

Tim Stuart, Andrew Butler, Paul Hoffman, Christoph Hafemeister, Efthymia Papalexi, William M. Mauck, Yuhan Hao, Marlon Stoeckius, Peter Smibert, Rahul Satija

Research output: Contribution to journalArticle

Abstract

Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to “anchor” diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.

Original languageEnglish (US)
Pages (from-to)1888-1902.e21
JournalCell
Volume177
Issue number7
DOIs
StatePublished - Jun 13 2019

Fingerprint

Small Cytoplasmic RNA
Anchors
Gene expression
Gene Expression
Lymphocytes
Atlases
Interneurons
Transcriptome
Chromatin
Bone
Bone Marrow
Technology
Datasets
Population
Proteins
Experiments

Keywords

  • integration
  • multi-modal
  • scATAC-seq
  • scRNA-seq
  • single cell
  • single-cell ATAC sequencing
  • single-cell RNA sequencing

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., ... Satija, R. (2019). Comprehensive Integration of Single-Cell Data. Cell, 177(7), 1888-1902.e21. https://doi.org/10.1016/j.cell.2019.05.031

Comprehensive Integration of Single-Cell Data. / Stuart, Tim; Butler, Andrew; Hoffman, Paul; Hafemeister, Christoph; Papalexi, Efthymia; Mauck, William M.; Hao, Yuhan; Stoeckius, Marlon; Smibert, Peter; Satija, Rahul.

In: Cell, Vol. 177, No. 7, 13.06.2019, p. 1888-1902.e21.

Research output: Contribution to journalArticle

Stuart, T, Butler, A, Hoffman, P, Hafemeister, C, Papalexi, E, Mauck, WM, Hao, Y, Stoeckius, M, Smibert, P & Satija, R 2019, 'Comprehensive Integration of Single-Cell Data', Cell, vol. 177, no. 7, pp. 1888-1902.e21. https://doi.org/10.1016/j.cell.2019.05.031
Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM et al. Comprehensive Integration of Single-Cell Data. Cell. 2019 Jun 13;177(7):1888-1902.e21. https://doi.org/10.1016/j.cell.2019.05.031
Stuart, Tim ; Butler, Andrew ; Hoffman, Paul ; Hafemeister, Christoph ; Papalexi, Efthymia ; Mauck, William M. ; Hao, Yuhan ; Stoeckius, Marlon ; Smibert, Peter ; Satija, Rahul. / Comprehensive Integration of Single-Cell Data. In: Cell. 2019 ; Vol. 177, No. 7. pp. 1888-1902.e21.
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