Sierra is an R package designed for detecting differential transcript usage from polyA-captured single cell (sc)RNA-seq data. Sierra identifies coordinates of read pileups (i.e. peaks) and performs UMI counting, followed by differential usage analysis between defined cell populations. Please read the vignette for a demonstration on how to use this software.
To install Sierra on your local machine, open an R session and use the following commands:
install.packages("devtools")
devtools::install_github("VCCRI/Sierra", build = TRUE, build_vignettes = TRUE, build_opts = c("--no-resave-data", "--no-manual"))
The vignette contains a detailed walk-through of how to use Sierra. The vignette can be access from R using:
library(Sierra)
browseVignettes("Sierra")
If you have trouble building the vignette, an alternative is to view it on the wiki and install the R package without it:
devtools::install_github("VCCRI/Sierra", build = TRUE)
The manuscript describing Sierra, including validation and example applications, is published in Genome Biology.
Briefly, the Sierra pipeline requires as input a BAM file, such as produced by the 10x Genomics CellRanger software, the reference GTF file used for alignment and a BED file of junctions derived from the BAM file as produced by RegTools.
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Splice-aware peak calling is used to identify read pileups corresponding to potential polyA sites in the dataset.
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UMI counting is performed against a set of peak coordinates, first unified in the case of multiple experiments.
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Peak coordinates are annotated with various features, including the genomic features they fall on.
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Differential transcript usage (DTU) is evaluated between defined cell populations by applying the differential exon method DEXSeq to test for differences in the relative usage of peaks, with pseudo-bulk profiles of cells used to define replicates.
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DTU genes can be visualised using read coverage plots, or by plotting the relative expression of peaks.
If you find Sierra useful in your research, please cite the following paper:
Patrick, R., Humphreys, D.T., Janbandhu, V., Oshlack A., Ho J.W.K., Harvey, R.P. and Lo K.K. Sierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data. Genome Biol 21, 167 (2020). https://doi.org/10.1186/s13059-020-02071-7
Sierra is maintained by Ralph Patrick, David Humphreys and Kitty Lo. For questions or feedback you can contact them at:
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Ralph Patrick: ralph.patrick at imb dot uq dot edu dot au
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David Humphreys: d.humphreys at victorchang dot edu dot au
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Kitty Lo: kitty.lo at gmail dot com
For a command line version of Sierra that can be used, for example, in a high performance computing environment, see this implementation by Geert van Geest.