CReSCENT: CanceR Single Cell ExpressioN Toolkit
| Autor: | Hillary Elrick, Kevin L Lu, Mia Husić, Laura M. Richards, Parisa Shooshtari, Suluxan Mohanraj, Ping Luo, Samarth Patel, Erik Christensen, Danielle C Croucher, Alaine Naidas, Shaikh Rashid, Trevor J. Pugh, Arun K. Ramani, Prabnur Bal, Alaina Mahalanabis, J. Javier Díaz-Mejía, Martin D. Pham, Michael Brudno |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
AcademicSubjects/SCI00010 T-Lymphocytes Cell Biology 03 medical and health sciences Upload 0302 clinical medicine Neoplasms medicine Genetics Humans RNA-Seq Cancer biology 030304 developmental biology 0303 health sciences business.industry RNA Benchmarking Pipeline (software) Expression (mathematics) medicine.anatomical_structure Web Server Issue Scalability Single-Cell Analysis Software engineering business Software 030217 neurology & neurosurgery |
| Zdroj: | Nucleic Acids Research Paediatrics Publications |
| DOI: | 10.1101/2020.03.27.012740 |
| Popis: | CReSCENTCanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users. |
| Databáze: | OpenAIRE |
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