DestVI identifies continuums of cell types in spatial transcriptomics data

Romain Lopez; Baoguo Li; Hadas Keren-Shaul; Pierre Boyeau; Merav Kedmi; David Pilzer; Adam Jelinski; Ido Yofe; Eyal David; Allon Wagner; Can Ergen; Yoseph Addadi; Ofra Golani; Franca Ronchese; Michael I. Jordan; Ido Amit; Nir Yosef

doi:10.1038/s41587-022-01272-8

DestVI identifies continuums of cell types in spatial transcriptomics data

Romain Lopez, Baoguo Li, Hadas Keren-Shaul, Pierre Boyeau, Merav Kedmi, David Pilzer, Adam Jelinski, Ido Yofe, Eyal David, Allon Wagner, Can Ergen, Yoseph Addadi, Ofra Golani, Franca Ronchese, Michael I. Jordan, Ido Amit^*, Nir Yosef^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

100 Scopus citations

Abstract

Most spatial transcriptomics technologies are limited by their resolution, with spot sizes larger than that of a single cell. Although joint analysis with single-cell RNA sequencing can alleviate this problem, current methods are limited to assessing discrete cell types, revealing the proportion of cell types inside each spot. To identify continuous variation of the transcriptome within cells of the same type, we developed Deconvolution of Spatial Transcriptomics profiles using Variational Inference (DestVI). Using simulations, we demonstrate that DestVI outperforms existing methods for estimating gene expression for every cell type inside every spot. Applied to a study of infected lymph nodes and of a mouse tumor model, DestVI provides high-resolution, accurate spatial characterization of the cellular organization of these tissues and identifies cell-type-specific changes in gene expression between different tissue regions or between conditions. DestVI is available as part of the open-source software package scvi-tools (https://scvi-tools.org).

Original language	English
Pages (from-to)	1360-1369
Number of pages	10
Journal	Nature Biotechnology
Volume	40
Issue number	9
DOIs	https://doi.org/10.1038/s41587-022-01272-8
State	Published - Sep 2022
Externally published	Yes

Funding

Funders	Funder number
Helen and Martin Kimmel award for innovative investigation
ISF Israel Precision Medicine Program
Merck
IPMP
Wolfson Foundation and Family Charitable Trust
European Research Council
Achelis Foundation
Howard Hughes Medical Institute
Horizon 2020 Framework Programme	724471
Chan-Zuckerberg Foundation Network	2019–02452
National Institute of Mental Health	U19MH114821
National Institute of Allergy and Infectious Diseases	U19AI090023
Melanoma Research Alliance	509044
NeuroMac DFG/Transregional	PA-1604 08459
Israel Science Foundation	703/15

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Lopez, R., Li, B., Keren-Shaul, H., Boyeau, P., Kedmi, M., Pilzer, D., Jelinski, A., Yofe, I., David, E., Wagner, A., Ergen, C., Addadi, Y., Golani, O., Ronchese, F., Jordan, M. I., Amit, I., & Yosef, N. (2022). DestVI identifies continuums of cell types in spatial transcriptomics data. Nature Biotechnology, 40(9), 1360-1369. https://doi.org/10.1038/s41587-022-01272-8

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abstract = "Most spatial transcriptomics technologies are limited by their resolution, with spot sizes larger than that of a single cell. Although joint analysis with single-cell RNA sequencing can alleviate this problem, current methods are limited to assessing discrete cell types, revealing the proportion of cell types inside each spot. To identify continuous variation of the transcriptome within cells of the same type, we developed Deconvolution of Spatial Transcriptomics profiles using Variational Inference (DestVI). Using simulations, we demonstrate that DestVI outperforms existing methods for estimating gene expression for every cell type inside every spot. Applied to a study of infected lymph nodes and of a mouse tumor model, DestVI provides high-resolution, accurate spatial characterization of the cellular organization of these tissues and identifies cell-type-specific changes in gene expression between different tissue regions or between conditions. DestVI is available as part of the open-source software package scvi-tools (https://scvi-tools.org).",

author = "Romain Lopez and Baoguo Li and Hadas Keren-Shaul and Pierre Boyeau and Merav Kedmi and David Pilzer and Adam Jelinski and Ido Yofe and Eyal David and Allon Wagner and Can Ergen and Yoseph Addadi and Ofra Golani and Franca Ronchese and Jordan, {Michael I.} and Ido Amit and Nir Yosef",

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AU - Pilzer, David

AU - Jelinski, Adam

AU - Yofe, Ido

AU - David, Eyal

AU - Wagner, Allon

AU - Ergen, Can

AU - Addadi, Yoseph

AU - Golani, Ofra

AU - Ronchese, Franca

AU - Jordan, Michael I.

AU - Amit, Ido

AU - Yosef, Nir

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DestVI identifies continuums of cell types in spatial transcriptomics data

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