Over the last few years the number of methods for analysing scRNA-seq has exploded and there is now well over 200 software tools available. Each of these tools need to make a choice about how they store and represent the data used during their analysis. One attempt to standardise the data structures that are used is the SingleCellExperiment package created by Davide Risso and Aaron Lun, with help from Keegan Korthauer.

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The Bioconductor 3.7 release was announced this week. I thought I would have a look through the new packages and changes to existing packages and point out some of my highlights. The descriptions below are my summaries, if you want to see more detail you can read the full release notes here. Single-cell RNA-seq My interest is in single-cell RNA-seq analysis, so I am going to start off with packages related to this.

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For my PhD I am working on methods for analysing single-cell RNA-sequencing (scRNA-seq) data which measure the expression of genes in individual cells. One of the most common analyses done on this type of data is to cluster the cells, often in an attempt to find out what cell types are present in a sample. In a recent seminar I showed some images of what I am calling a “clustering tree” (you can see the slides here if you are interested).

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Luke Zappia

Bioinformatician in training

PhD student

Australia