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SinglePointRNA，一款用户友好型应用程序，实现了单细胞 RNA-seq 分析软件。

SinglePointRNA, an user-friendly application implementing single cell RNA-seq analysis software.

机构信息

Departamento de Bioquímica, Facultad de Medicina, Universidad Autónoma de Madrid (UAM), Madrid, Spain.

Genomics Unit Cantoblanco, Fundación Parque Científico de Madrid, Madrid, Spain.

出版信息

PLoS One. 2024 Jun 18;19(6):e0300567. doi: 10.1371/journal.pone.0300567. eCollection 2024.

DOI:10.1371/journal.pone.0300567
PMID:38889133
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11185446/
Abstract

Single-cell transcriptomics techniques, such as scRNA-seq, attempt to characterize gene expression profiles in each cell of a heterogeneous sample individually. Due to growing amounts of data generated and the increasing complexity of the computational protocols needed to process the resulting datasets, the demand for dedicated training in mathematical and programming skills may preclude the use of these powerful techniques by many teams. In order to help close that gap between wet-lab and dry-lab capabilities we have developed SinglePointRNA, a shiny-based R application that provides a graphic interface for different publicly available tools to analyze single cell RNA-seq data. The aim of SinglePointRNA is to provide an accessible and transparent tool set to researchers that allows them to perform detailed and custom analysis of their data autonomously. SinglePointRNA is structured in a context-driven framework that prioritizes providing the user with solid qualitative guidance at each step of the analysis process and interpretation of the results. Additionally, the rich user guides accompanying the software are intended to serve as a point of entry for users to learn more about computational techniques applied to single cell data analysis. The SinglePointRNA app, as well as case datasets for the different tutorials are available at www.github.com/ScienceParkMadrid/SinglePointRNA.

摘要

单细胞转录组学技术，如 scRNA-seq，试图单独描述异质样本中每个细胞的基因表达谱。由于生成的数据量不断增加，以及处理由此产生的数据集所需的计算协议的复杂性不断增加，对数学和编程技能的专门培训的需求可能会使许多团队无法使用这些强大的技术。为了帮助缩小湿实验室和干实验室能力之间的差距，我们开发了 SinglePointRNA，这是一个基于 shiny 的 R 应用程序，它为不同的公开可用工具提供了一个图形界面，用于分析单细胞 RNA-seq 数据。SinglePointRNA 的目的是为研究人员提供一个易于访问和透明的工具集，使他们能够自主地对其数据进行详细和自定义的分析。SinglePointRNA 采用上下文驱动的框架构建，优先在分析过程的每个步骤以及结果的解释中为用户提供可靠的定性指导。此外，随软件提供的丰富用户指南旨在作为用户学习应用于单细胞数据分析的计算技术的切入点。SinglePointRNA 应用程序以及不同教程的案例数据集可在 www.github.com/ScienceParkMadrid/SinglePointRNA 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/43571d29fb03/pone.0300567.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/50adc179cbb6/pone.0300567.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/6b8f22f5d9a3/pone.0300567.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/d91a53e9893e/pone.0300567.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/68dda8581a7e/pone.0300567.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/43571d29fb03/pone.0300567.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/50adc179cbb6/pone.0300567.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/6b8f22f5d9a3/pone.0300567.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/d91a53e9893e/pone.0300567.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/68dda8581a7e/pone.0300567.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03a/11185446/43571d29fb03/pone.0300567.g005.jpg

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The reactome pathway knowledgebase 2022.反应体通路知识库2022版。
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SCHNAPPs - Single Cell sHiNy APPlication(s).SCHNAPPs - 单细胞 sHiNy 应用程序。
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