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ABSTRACT: Background
Single-cell RNA sequencing (scRNA-seq) enables the high-throughput quantification of transcriptional profiles in single cells. In contrast to bulk RNA-seq, additional preprocessing steps such as cell barcode identification or unique molecular identifier (UMI) deconvolution are necessary for preprocessing of data from single cell protocols. R packages that can easily preprocess data and rapidly visualize quality metrics and read alignments for individual cells across multiple samples or runs are still lacking.Results
Here we present scruff, an R/Bioconductor package that preprocesses data generated from the CEL-Seq or CEL-Seq2 protocols and reports comprehensive data quality metrics and visualizations. scruff rapidly demultiplexes, aligns, and counts the reads map
SUBMITTER: Wang Z
PROVIDER: S-EPMC6498700 | biostudies-literature | 2019 May
REPOSITORIES: biostudies-literature