Beta-Poisson model for single-cell RNA-seq data analyses

Vu, Trung Nghia, Wills, Quin F., Kalari, Krishna R., Niu, Nifang, Wang, Liewei, Rantalainen, Mattias, Pawitan, Yudi·2016·Bioinformatics
DOI 10.1093/bioinformatics/btw202

Cited by (163)

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  42. CASi: A multi-timepoint scRNAseq data analysis framework
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  43. Additional file 2 of IDEAS: individual level differential expression analysis for single-cell RNA-seq data
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  48. Additional file 3 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data
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  49. Additional file 5 of PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data
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  52. Additional file 1 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data
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  53. Additional file 3 of IDEAS: individual level differential expression analysis for single-cell RNA-seq data
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  54. Additional file 2 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data
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  55. Additional file 5 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data
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  58. Systematic comparison and optimization of parameter estimation methods for stochastic gene expression kinetics
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