DECOMICS 是一款闪亮的应用程序,用于对大量 omic 数据进行无监督细胞类型解卷积和生物学解释。

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2024-09-20 eCollection Date: 2024-01-01 DOI:10.1093/bioadv/vbae136
Slim Karkar, Ashwini Sharma, Carl Herrmann, Yuna Blum, Magali Richard
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引用次数: 0

摘要

摘要:无监督解卷积算法常用于估算大量组织样本中的细胞成分。然而,应用细胞类型解卷积和解释结果仍然是一项挑战,如果没有生物信息学方面的培训,就更是如此。在这里,我们提出了一种从大块转录组或甲基组中估计和识别细胞类型组成的工具。DECOMICS 是一个闪亮的网络应用程序,专门用于对大容量 omic 数据进行无监督解卷积。它提供(i)多种现有算法,用于对基因表达或甲基化水平矩阵进行解卷积;(ii)一个富集分析模块,用于根据富集分析帮助对解卷积成分进行生物学解释;以及(iii)一些可视化工具。输入数据可以 csv 格式下载,并在网络应用程序中进行预处理(归一化、转换和特征选择)。解卷积、富集和可视化过程的结果可以下载:DECOMICS是一个R-shiny网络应用程序,可(i)使用此处提供的R软件包直接从本地R会话启动:https://gitlab.in2p3.fr/Magali.Richard/decomics(可通过本地安装或通过我们提供的虚拟机和Docker镜像);或(ii)在生物圈-IFB生命科学云联盟(一个可扩展的高性能计算多云环境)中启动:https://biosphere.france-bioinformatique.fr/catalogue/appliance/193/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data.

Summary: Unsupervised deconvolution algorithms are often used to estimate cell composition from bulk tissue samples. However, applying cell-type deconvolution and interpreting the results remain a challenge, even more without prior training in bioinformatics. Here, we propose a tool for estimating and identifying cell type composition from bulk transcriptomes or methylomes. DECOMICS is a shiny-web application dedicated to unsupervised deconvolution approaches of bulk omic data. It provides (i) a variety of existing algorithms to perform deconvolution on the gene expression or methylation-level matrix, (ii) an enrichment analysis module to aid biological interpretation of the deconvolved components, based on enrichment analysis, and (iii) some visualization tools. Input data can be downloaded in csv format and preprocessed in the web application (normalization, transformation, and feature selection). The results of the deconvolution, enrichment, and visualization processes can be downloaded.

Availability and implementation: DECOMICS is an R-shiny web application that can be launched (i) directly from a local R session using the R package available here: https://gitlab.in2p3.fr/Magali.Richard/decomics (either by installing it locally or via a virtual machine and a Docker image that we provide); or (ii) in the Biosphere-IFB Clouds Federation for Life Science, a multi-cloud environment scalable for high-performance computing: https://biosphere.france-bioinformatique.fr/catalogue/appliance/193/.

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