SEQUIN: rapid and reproducible analysis of RNA-seq data in R/Shiny Article Swipe
Claire Weber
,
Marissa B. Hirst
,
Ben Ernest
,
Hannah M. Baskir
,
Carlos A. Tristan
,
Pei‐Hsuan Chu
,
Ilyas Singeç
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.02.23.481646
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.02.23.481646
SEQUIN is a new web application (app) that allows fast and intuitive RNA-sequencing data analysis for organisms, tissues, and single cells. Integrated app functions enable uploading datasets, quality control, gene set enrichment, data visualization, and differential gene expression analysis. We also present the iPSC Profiler, a practical tool that helps to measure pluripotency and cell differentiation. Freely available to the public, SEQUIN empowers scientists to investigate transcriptome data firsthand with cutting edge statistical methods.
Related Topics
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2022.02.23.481646
- https://www.biorxiv.org/content/biorxiv/early/2022/02/24/2022.02.23.481646.full.pdf
- OA Status
- green
- Cited By
- 1
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4213457561
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4213457561Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2022.02.23.481646Digital Object Identifier
- Title
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SEQUIN: rapid and reproducible analysis of RNA-seq data in R/ShinyWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-02-24Full publication date if available
- Authors
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Claire Weber, Marissa B. Hirst, Ben Ernest, Hannah M. Baskir, Carlos A. Tristan, Pei‐Hsuan Chu, Ilyas SingeçList of authors in order
- Landing page
-
https://doi.org/10.1101/2022.02.23.481646Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2022/02/24/2022.02.23.481646.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://www.biorxiv.org/content/biorxiv/early/2022/02/24/2022.02.23.481646.full.pdfDirect OA link when available
- Concepts
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Upload, Visualization, Computer science, Transcriptome, Set (abstract data type), RNA-Seq, Computational biology, Data set, RNA, Measure (data warehouse), Biology, Gene, Data mining, Gene expression, World Wide Web, Genetics, Artificial intelligence, Programming languageTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2022: 1Per-year citation counts (last 5 years)
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20Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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