دورية أكاديمية
M3S: a comprehensive model selection for multi-modal single-cell RNA sequencing data
| العنوان: | M3S: a comprehensive model selection for multi-modal single-cell RNA sequencing data |
|---|---|
| المؤلفون: | Yu Zhang, Changlin Wan, Pengcheng Wang, Wennan Chang, Yan Huo, Jian Chen, Qin Ma, Sha Cao, Chi Zhang |
| المصدر: | BMC Bioinformatics, Vol 20, Iss S24, Pp 1-5 (2019) |
| بيانات النشر: | BMC, 2019. |
| سنة النشر: | 2019 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Biology (General) |
| مصطلحات موضوعية: | Single cell RNA-seq, Multimodality, Differential gene expression analysis, Drop-seq, Left truncated mixture Gaussian, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5 |
| الوصف: | Abstract Background Various statistical models have been developed to model the single cell RNA-seq expression profiles, capture its multimodality, and conduct differential gene expression test. However, for expression data generated by different experimental design and platforms, there is currently lack of capability to determine the most proper statistical model. Results We developed an R package, namely Multi-Modal Model Selection (M3S), for gene-wise selection of the most proper multi-modality statistical model and downstream analysis, useful in a single-cell or large scale bulk tissue transcriptomic data. M3S is featured with (1) gene-wise selection of the most parsimonious model among 11 most commonly utilized ones, that can best fit the expression distribution of the gene, (2) parameter estimation of a selected model, and (3) differential gene expression test based on the selected model. Conclusion A comprehensive evaluation suggested that M3S can accurately capture the multimodality on simulated and real single cell data. An open source package and is available through GitHub at https://github.com/zy26/M3S. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1471-2105 |
| Relation: | https://doaj.org/toc/1471-2105 |
| DOI: | 10.1186/s12859-019-3243-1 |
| URL الوصول: | https://doaj.org/article/fa5c57a58ff64adaa20df927ac574689 |
| رقم الأكسشن: | edsdoj.fa5c57a58ff64adaa20df927ac574689 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 14712105 |
|---|---|
| DOI: | 10.1186/s12859-019-3243-1 |