UCSC Cell Browser: visualize your single-cell data
| Autor: | Lucas Seninge, W. James Kent, Alex A. Pollen, Pablo Moreno, Brian J. Raney, Nikolay S. Markov, Matthew L. Speir, Maximilian Haeussler, Aparna Bhaduri, Irene Papatheodorou, Tomasz J. Nowakowski |
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| Přispěvatelé: | Kendziorski, Christina |
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
AcademicSubjects/SCI01060 Computer science Bioinformatics Gene Expression Biochemistry Mathematical Sciences World Wide Web 03 medical and health sciences Databases 0302 clinical medicine Genetic Information and Computing Sciences Genetics Molecular Biology Metadata annotation 030304 developmental biology computer.programming_language Supplementary data 0303 health sciences Metadata Genomics Python (programming language) Biological Sciences Applications Notes Computer Science Applications Computational Mathematics ComputingMethodologies_PATTERNRECOGNITION Computational Theory and Mathematics Generic health relevance computer 030217 neurology & neurosurgery Software |
| Zdroj: | Bioinformatics (Oxford, England), vol 37, iss 23 Bioinformatics |
| Popis: | Summary As the use of single-cell technologies has grown, so has the need for tools to explore these large, complicated datasets. The UCSC Cell Browser is a tool that allows scientists to visualize gene expression and metadata annotation distribution throughout a single-cell dataset or multiple datasets. Availability and implementation We provide the UCSC Cell Browser as a free website where scientists can explore a growing collection of single-cell datasets and a freely available python package for scientists to create stable, self-contained visualizations for their own single-cell datasets. Learn more at https://cells.ucsc.edu. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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