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scCancer: a package for automated processing of single-cell RNA-seq data in cancer.
- Source :
-
Briefings in bioinformatics [Brief Bioinform] 2021 May 20; Vol. 22 (3). - Publication Year :
- 2021
-
Abstract
- Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis and treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer cell heterogeneities and microenvironments at single-cell transcriptomic level. Here, we develop an R package named scCancer, which focuses on processing and analyzing scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features. Firstly, the package introduced comprehensive quality control metrics. Secondly, it used a data-driven machine learning algorithm to accurately identify major cancer microenvironment cell populations. Thirdly, it estimated a malignancy score to classify malignant (cancerous) and non-malignant cells. Then, it analyzed intra-tumor heterogeneities by key cellular phenotypes (such as cell cycle and stemness), gene signatures and cell-cell interactions. Besides, it provided multi-sample data integration analysis with different batch-effect correction strategies. Finally, user-friendly graphic reports were generated for all the analyses. By testing on 56 samples with 433 405 cells in total, we demonstrated its good performance. The package is available at: http://lifeome.net/software/sccancer/.<br /> (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
Details
- Language :
- English
- ISSN :
- 1477-4054
- Volume :
- 22
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Briefings in bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 34020534
- Full Text :
- https://doi.org/10.1093/bib/bbaa127