Bioinformatics Seminars

Bioinformatics Seminar

Time: 11AM
Venue: Zoom Webinar

2 March 2021

Beyond single sample applications in single cell RNA-seq

Belinda Phipson
Peter Mac

Single cell RNA Sequencing (scRNA-seq) has rapidly gained popularity over the last few years for profiling the transcriptomes of thousands of single cells. As the technology has matured, there is a shift towards applications comparing cell type composition and gene expression of samples between experimental conditions. In the context of bulk RNA-seq, the main goal of analysis between multiple groups is to find significant differentially expressed genes. It has not been possible to deconvolve the difference between genes that are lowly expressed across the majority of cells making up a sample and genes that are highly expressed in a small proportion of cells. With scRNA-seq data we can now directly compare the relative cell type composition of samples between conditions. Due to differences in capture efficiency and dissociation protocols, there is natural variation in cell type proportion estimates. In addition, in a designed experiment with multiple samples, there is additional variability due to biological (sample-to-sample) variation. This additional biological variability needs to be taken into account when testing for differences in cell type proportions between conditions. In this talk I will demonstrate my approach to analysing a relatively large (>54,000) heterogeneous single nuclei heart dataset with a focus on how we find statistically significant changes in cell type proportions between fetal, young and adult heart biopsy samples.

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