Single-cell transcriptomics with Oxford Nanopore: data analysis
Event overview
During this Knowledge Exchange, John Beaulaurier presented the Oxford Nanopore Technologies Sockeye analysis pipeline for demultiplexing cell barcodes and UMIs from long single-cell nanopore reads.
John guided users through the process of demultiplexing and conducting preliminary analyses on sequencing data produced from the Oxford Nanopore Technologies “Single-cell transcriptomics with cDNA prepared using 10X Genomics Protocol”. These steps are performed using the Sockeye open-source bioinformatic pipeline, which can now be executed via the wf-single-cell workflow in EPI2ME Labs. This workflow is designed to recover cell barcode and UMI sequences from the nanopore reads, as well as generate some basic outputs describing the composition of the single-cell sequencing data.
During the course of walking through an example Sockeye run, viewers will learn:
- What kind of sequencing data to expect from the single-cell sequencing protocol
- How to install, configure, and run the EPI2ME Labs wf-single-cell workflow
- What primary and intermediate output files are generated by various steps during the pipeline run
- FAQs and considerations when examining output files
Meet the speaker
John Beaulaurier is a Genomic Applications Bioinformatics Manager at Oxford Nanopore, where he leads a team of bioinformatics scientists focused on collaborative projects designed to highlight the unique capabilities of nanopore sequencing technology. During his four years with Oxford Nanopore, he has worked on a wide variety of projects, including viral & bacterial metagenomics, DNA methylation, immunogenomics, and antibody repertoire sequencing. Most recently, he has developed the Sockeye bioinformatic pipeline for demultiplexing Oxford Nanopore reads sequenced from single-cell transcriptome libraries. Prior to joining Oxford Nanopore, he completed a PhD in Biomedical Sciences at the Icahn School of Medicine at Mount Sinai, where he focused on computational challenges associated with long-read metagenomics and bacterial DNA modifications.
