.png){kind=icon}
返回
Simulating multiple variability in spatially resolved transcriptomics with scCube
.png){kind=icon}
OA
AI
DOI：10.1038/s41467-024-49445-0.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the computational methods. A widely-used approach involves utilizing simulated data. However, biases exist in terms of the currently available simulated SRT data, which seriously affects the accuracy of method evaluation and validation. Herein, we present scCube (https://github.com/ZJUFanLab/scCube), a Python package for independent, reproducible, and technology-diverse simulation of SRT data. scCube not only enables the preservation of spatial expression patterns of genes in reference-based simulations, but also generates simulated data with different spatial variability (covering the spatial pattern type, the resolution, the spot arrangement, the targeted gene type, and the tissue slice dimension, etc.) in reference-free simulations. We comprehensively benchmark scCube with existing single-cell or SRT simulators, and demonstrate the utility of scCube in benchmarking spot deconvolution, gene imputation, and resolution enhancement methods in detail through three applications. Unbiasedly benchmarking SRT computational methods remains a pressing challenge. Here, authors develop scCube, a simulation framework enabling scalable, reproducible, and unbiased generation of simulated SRT data, allowing researchers to benchmark and evaluate different methods.
Keyword:
SINGLE-CELL
GENE-EXPRESSION
ATLAS
IDENTIFICATION
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
15.7
论文数:
9.3W
被引数:
91.2W
机构
引用论文
DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligenceDSTG: 通过基于图形的人工智能对空间转录组数据进行反卷积OAAI
OAAI分享收藏Identification of spatial expression trends in single-cell gene expression data单细胞基因表达数据中空间表达趋势的识别.png)
NATURE METHODSOAAI
NATURE METHODSIF32.1
OAAI分享收藏A single-cell and spatially resolved atlas of human breast cancers人类乳腺癌的单细胞和空间分辨图谱NATURE GENETICSOAAI
NATURE GENETICSIF31.8
OAAI分享收藏分享收藏Uranium release from different size fractions of sediments in Hanford 300 area, Washington, USA
PREAI
分享收藏
查看更多内容