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DestVI identifies continuums of cell types in spatial transcriptomics data

Standard

DestVI identifies continuums of cell types in spatial transcriptomics data. / Lopez, Romain; Li, Baoguo; Keren-Shaul, Hadas; Boyeau, Pierre; Kedmi, Merav; Pilzer, David; Jelinski, Adam; Yofe, Ido; David, Eyal; Wagner, Allon; Ergen, Can; Addadi, Yoseph; Golani, Ofra; Ronchese, Franca; Jordan, Michael I; Amit, Ido; Yosef, Nir.

in: NAT BIOTECHNOL, Jahrgang 40, Nr. 9, 09.2022, S. 1360-1369.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

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, MI, Amit, I & Yosef, N 2022, 'DestVI identifies continuums of cell types in spatial transcriptomics data', NAT BIOTECHNOL, Jg. 40, Nr. 9, S. 1360-1369. https://doi.org/10.1038/s41587-022-01272-8

APA

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. NAT BIOTECHNOL, 40(9), 1360-1369. https://doi.org/10.1038/s41587-022-01272-8

Vancouver

Lopez R, Li B, Keren-Shaul H, Boyeau P, Kedmi M, Pilzer D et al. DestVI identifies continuums of cell types in spatial transcriptomics data. NAT BIOTECHNOL. 2022 Sep;40(9):1360-1369. https://doi.org/10.1038/s41587-022-01272-8

Bibtex

@article{1a17ad9304204d00ab1e08289c4d0502,
title = "DestVI identifies continuums of cell types in spatial transcriptomics data",
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 ).",
keywords = "Animals, Gene Expression Profiling/methods, Mice, Neoplasms/genetics, Single-Cell Analysis/methods, Software, Transcriptome/genetics, Exome Sequencing",
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",
note = "{\textcopyright} 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.",
year = "2022",
month = sep,
doi = "10.1038/s41587-022-01272-8",
language = "English",
volume = "40",
pages = "1360--1369",
journal = "NAT BIOTECHNOL",
issn = "1087-0156",
publisher = "NATURE PUBLISHING GROUP",
number = "9",

}

RIS

TY - JOUR

T1 - DestVI identifies continuums of cell types in spatial transcriptomics data

AU - Lopez, Romain

AU - Li, Baoguo

AU - Keren-Shaul, Hadas

AU - Boyeau, Pierre

AU - Kedmi, Merav

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

N1 - © 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.

PY - 2022/9

Y1 - 2022/9

N2 - 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 ).

AB - 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 ).

KW - Animals

KW - Gene Expression Profiling/methods

KW - Mice

KW - Neoplasms/genetics

KW - Single-Cell Analysis/methods

KW - Software

KW - Transcriptome/genetics

KW - Exome Sequencing

U2 - 10.1038/s41587-022-01272-8

DO - 10.1038/s41587-022-01272-8

M3 - SCORING: Journal article

C2 - 35449415

VL - 40

SP - 1360

EP - 1369

JO - NAT BIOTECHNOL

JF - NAT BIOTECHNOL

SN - 1087-0156

IS - 9

ER -