计算生物学
计算机科学
细胞
组学
生物
生物信息学
遗传学
作者
Lu Pan,Bufu Tang,Xuan Zhang,Paolo Parini,Roman Tremmel,Joseph Loscalzo,Volker M. Lauschke,Bradley A. Maron,Paola Paci,Ingemar Ernberg,Nguan Soon Tan,Ákos Végvári,Zehuan Liao,Sundararaman Rengarajan,Roman A. Zubarev,Yuxuan Fan,Zheng Xu,Xiaojie Jian,Ren Sheng,Zhenning Wang
出处
期刊:iMeta
[Wiley]
日期:2025-04-28
摘要
Abstract The rapid advancement of multi‐omics single‐cell technologies has significantly enhanced our ability to investigate complex biological systems at unprecedented resolution. However, many existing analysis tools are complex, requiring substantial coding expertize, which can be a barrier for computationally less competent researchers. To address this challenge, we present single‐cell analyst, a user‐friendly, web‐based platform to facilitate comprehensive multi‐omics analysis. Single‐cell analyst supports a wide range of data types, including six single‐cell omics: single‐cell RNA sequencing (scRNA‐sequencing), single‐cell assay for transposase accessible chromatin sequencing (scATAC‐seq sequencing), single‐cell immune profiling (scImmune profiling), single‐cell copy number variation, cytometry by time‐of‐flight, and flow cytometry and spatial transcriptomics, and enables researchers to perform integrated analyses without requiring programming skills. The platform offers both online and offline modes, providing flexibility for various use cases. It automates critical analysis steps, such as quality control, data processing, and phenotype‐specific analyses, while also offering interactive, publication‐ready visualizations. With over 20 interactive tools for intermediate analysis, single cell analyst simplifies workflows and significantly reduces the learning curve typically associated with similar platforms. This robust tool accommodates datasets of varying sizes, completing analyses within minutes to hours depending on the data volume, and ensures efficient use of computational resources. By democratizing the complex process of multi‐omics analysis, single‐cell analyst serves as an accessible, all‐encompassing solution for researchers of diverse technical backgrounds. The platform is freely accessible at www.singlecellanalyst.org .