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Welcome to the SCAPE wiki

SCAPE (Single Cell Alternative Polyadenylation using Expectation-maximization) is a tool to explore alternative polyadenylation at single cell level based 3'-tag sequencing data.

Some jargons

• pA site: polyadenylation site.
• APA: alternative polyadenylation.
• polyA: a stretch of A residues.

General introduction

SCAPE models the scRNA-seq data as a mixture of K isoform components and one noise component, i.e. a read either comes from an APA isoform or belongs to noise. The $i$ th ($i = 1…K$) isoform component has three parameters: (a) the mean position of the pA site $α_i$, (b) the standard deviation (std) of the pA site$ β_i$, (c) the weight or proportion $π_i$. The number of components is automatically selected using Bayesian Information Criterion (BIC). We use the Expectation-Maximization (EM) algorithm and numerical optimization to infer the parameters.

Examples

• SCAPE toy example (simulated dataset)
• Pair-end scRNAseq datasets (Microwell-seq)
• Single-end scRNAseq datasets (10X genomics)
• Differential APA analysis (Mouse brain vs bone marrow, R)
• APA dynamics analysis (mouse HSC, R)

Other topics

• Change default parameters of SCAPE
• Estimate insert size distribution from scRNA-seq data (mouse scRNA-seq example)
• Estimate polyA length distribution from scRNA-seq data (mouse scRNA-seq example)

Questions

Visit issues or contact @zhou-ran regarding bioinformatics issues, @chengl7 regarding statistics/algorithm issues.