小柯机器人

美国加州大学伯克利分校Nir Yosef、以色列魏兹曼科学研究所Ido Amit等研究人员，合作利用DestVI揭示空间转录组学数据中细胞类型的连续性。相关论文于2022年4月21日在线发表在《自然—生物技术》杂志上。

为了确定同一类型的细胞内转录组的连续变化，研究人员开发了DestVI。通过模拟，研究人员证明DestVI在估计每个斑点内每个细胞类型的基因表达方面优于现有方法。应用于感染淋巴结和小鼠肿瘤模型的研究，DestVI提供了这些组织的细胞组织的高分辨率、准确的空间特征，并确定了不同组织区域之间或不同条件下基因表达的细胞类型特定变化。DestVI可作为开源软件包scvi-tools（https://scvi-tools.org）的一部分。

据介绍，大多数空间转录组学技术都受到其分辨率的限制，其斑点大小大于单细胞的大小。虽然与单细胞RNA测序的联合分析可以缓解这个问题，但目前的方法仅限于评估离散的细胞类型，可揭示每个斑点内的细胞类型比例。

附：英文原文

Title: DestVI identifies continuums of cell types in spatial transcriptomics data

Author: 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

Issue&Volume: 2022-04-21

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 ). DestVI models continuous cell states in spatial transcriptomics data.

DOI: 10.1038/s41587-022-01272-8

Source: https://www.nature.com/articles/s41587-022-01272-8

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex