New protocols and computational tools for scRNAseq analysis

Abstract

The fast development of single cell RNA sequencing (scRNAseq) presents new challenges in data analysis and opportunities for protocol development. To address challenges in data preprocessing, I developed scPipe, an R/Bioconductor package that integrates barcode demultiplexing, read alignment, UMI-aware gene-level quantification and quality control of raw sequencing data generated by multiple protocols. Results from scPipe can be used as input for downstream analyses and can be easily incorporated into R-based pipelines with other tools. In order to compare different computational methods for scRNAseq data, I generated a realistic benchmark experiment that included single cells and admixtures..