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psupertime is pseudotime ordering for single cell RNA-seq data with sequential labels
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👋 Hello User! 👋

psupertime is an R package which uses single cell RNAseq data, where the cells have labels following a known sequence (e.g. a time series), to identify a small number of genes which place cells in that known order. It can be used for discovery of relevant genes, for exploration of unlabelled data, and assessment of one dataset with respect to the labels known for another dataset.

Read the pre-print here:

How to install / use

To use this development version of the package, run the following lines in R:

devtools::install_github('wmacnair/psupertime', build_vignettes=TRUE)

(You may need to install the package remotes, with install.packages('remotes'). Installation took <90s on a Macbook Pro.)

This should load all of the code and relevant documentation.

Basic analyses

We have included a small dataset which allows you to use some of the basic functionality in psupertime. To do this, have a look at the vignettes:

browseVignettes(package = 'psupertime')

psupertime is fast: running these analyses took a bit under 1 minute on a Macbook Pro. The vignette also describes some of the additional functionality you can use, and full details are given in the documentation, via ?psupertime.

Replicating analyses in the manuscript

To keep this main package light, we have only included a small example dataset. To replicate the figures in the manuscript and provide additional datasets for user experimentation, we have also made a data package, psupplementary. If you would like to see in more detail what psupertime can do, please go here.

Development roadmap

At the moment, psupertime takes a SingleCellExperiment/sce object as an input, and returns a psupertime object. I want to make this a bit smoother for users, by integrating the outputs from psupertime into the row and column annotations of the sce. So for example, the gene coefficients would be stored in rowData, and the latent time estimates would be stored in colData. I'll also add some unit tests and submit to Bioconductor.


Please add any issues or requests to the Issues page. All feedback enthusiastically received.



System requirements

psupertime requires R (>= 3.4.3), and the following dependencies: ggplot2 3.1.1, data.table 1.12.2, glmnet 2.0-16, scales 1.0.0, stringr 1.4.0, scran 1.10.2, SingleCellExperiment 1.4.1, SummarizedExperiment 1.12.0, RColorBrewer 1.1-2.

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