Journal article
Processing single-cell RNA-seq datasets using SingCellaR
- Abstract:
- Single-cell RNA sequencing has led to unprecedented levels of data complexity. Although several computational platforms are available, performing data analyses for multiple datasets remains a significant challenge. Here, we provide a comprehensive analytical protocol to interrogate multiple datasets on SingCellaR, an analysis package in R. This tool can be applied to general single-cell transcriptome analyses. We demonstrate steps for data analyses and visualization using bespoke pipelines, in conjunction with existing analysis tools to study human hematopoietic stem and progenitor cells. For complete details on the use and execution of this protocol, please refer to Roy et al. (2021).
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 7.1MB, Terms of use)
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- Publisher copy:
- 10.1016/j.xpro.2022.101266
Authors
- Publisher:
- Cell Press
- Journal:
- STAR Protocols More from this journal
- Volume:
- 3
- Issue:
- 2
- Article number:
- 101266
- Publication date:
- 2022-04-01
- Acceptance date:
- 2022-04-01
- DOI:
- EISSN:
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2666-1667
- Pmid:
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35391938
- Language:
-
English
- Keywords:
- Pubs id:
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1250813
- Local pid:
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pubs:1250813
- Deposit date:
-
2022-11-15
Terms of use
- Copyright holder:
- Wang et al.
- Copyright date:
- 2022
- Rights statement:
- Copyright 2022 The Author(s). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
- Licence:
- CC Attribution (CC BY)
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