Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst
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 c...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | iMeta |
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| Online Access: | https://doi.org/10.1002/imt2.70038 |
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| author | 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 Zubarev Yuxuan Fan Xu Zheng Xinyue Jian Ren Sheng Zhenning Wang Xuexin Li |
| author_facet | 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 Zubarev Yuxuan Fan Xu Zheng Xinyue Jian Ren Sheng Zhenning Wang Xuexin Li |
| author_sort | Lu Pan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-32effa28d0124cbfa969e5101ac52d85 |
| institution | OA Journals |
| issn | 2770-596X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | iMeta |
| spelling | doaj-art-32effa28d0124cbfa969e5101ac52d852025-08-20T02:24:23ZengWileyiMeta2770-596X2025-06-0143n/an/a10.1002/imt2.70038Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analystLu Pan0Bufu Tang1Xuan Zhang2Paolo Parini3Roman Tremmel4Joseph Loscalzo5Volker M. Lauschke6Bradley A. Maron7Paola Paci8Ingemar Ernberg9Nguan Soon Tan10Ákos Végvári11Zehuan Liao12Sundararaman Rengarajan13Roman Zubarev14Yuxuan Fan15Xu Zheng16Xinyue Jian17Ren Sheng18Zhenning Wang19Xuexin Li20Institute of Environmental Medicine Karolinska Institutet Solna SwedenDepartment of Radiation Oncology Zhongshan Hospital Affiliated to Fudan University Shanghai ChinaDepartment of Colorectal Surgery, Yunnan Cancer Hospital The Third Affiliated Hospital of Kunming Medical University Kunming Yunnan ChinaCardio Metabolic Unit, Department of Medicine, and Department of Laboratory Medicine Karolinska Institutet Stockholm SwedenUniversity of Tuebingen Tuebingen GermanyDepartment of Medicine, Brigham and Women's Hospital Harvard Medical School Boston Massachusetts USADepartment of Physiology and Pharmacology Karolinska Institutet Solna SwedenDepartment of Medicine, Brigham and Women's Hospital Harvard Medical School Boston Massachusetts USADepartment of Computer, Control and Management Engineering Sapienza University of Rome Rome ItalyDepartment of Microbiology, Tumor and Cell Biology Karolinska Institutet Solna SwedenSchool of Biological Sciences Nanyang Technological University Singapore SingaporeDepartment of Medical Biochemistry and Biophysics Karolinska Institutet Solna SwedenDepartment of Microbiology, Tumor and Cell Biology Karolinska Institutet Solna SwedenDepartment of Physical Therapy, Movement & Rehabilitation Sciences Northeastern University Boston Massachusetts USADepartment of Medical Biochemistry and Biophysics Karolinska Institutet Solna SwedenChina Medical University‐The Queen's University of Belfast Joint College China Medical University Shenyang Liaoning ChinaBiomedical Innovation Center, The Fourth Affiliated Hospital China Medical University Shenyang Liaoning ChinaBiomedical Innovation Center, The Fourth Affiliated Hospital China Medical University Shenyang Liaoning ChinaCollege of Life and Health Sciences Northeastern University Shenyang Liaoning ChinaKey Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education China Medical University Shenyang Liaoning ChinaDepartment of General Surgery, The Fourth Affiliated Hospital China Medical University Shenyang Liaoning ChinaAbstract 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.https://doi.org/10.1002/imt2.70038multi‐omicssingle‐cell sequencingweb server |
| spellingShingle | 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 Zubarev Yuxuan Fan Xu Zheng Xinyue Jian Ren Sheng Zhenning Wang Xuexin Li Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst iMeta multi‐omics single‐cell sequencing web server |
| title | Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst |
| title_full | Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst |
| title_fullStr | Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst |
| title_full_unstemmed | Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst |
| title_short | Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst |
| title_sort | comprehensive analysis of multi omics single cell data using the single cell analyst |
| topic | multi‐omics single‐cell sequencing web server |
| url | https://doi.org/10.1002/imt2.70038 |
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