Multi-cell RNA-Seq: A computational approach

Cazaubiel, Jules; Tourtillott, Nicholas

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Multi-cell RNA-Seq: A computational approach

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RNA sequencing has expanded nearly exponentially over the past decade and has allowed scientists an intimate glimpse into the expression patterns of cells and tissues. These techniques come in two main forms: bulk tissue RNA seq which captures a wide array of transcripts at a shallow depth across a tissue sample and single cell RNA seq which captures transcripts at a greater depth and tags them to individual cells. Here we present Multicell RNA-Seq, a pipeline of bioinformatics tools which together can be used to bridge the gap between bulk tissue and single cell techniques. Our approach allowed us to map specific transcript isoforms to single cell clusters and identify clustering levels beyond which transcript isoforms are no longer detectable within a single cell dataset.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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