The EWCE
R package is designed to facilitate expression weighted cell
type enrichment analysis as described in our Frontiers in Neuroscience
paper.1 EWCE
can be applied to any gene list.
Using EWCE
essentially involves two steps:
- Prepare a single-cell reference; i.e. CellTypeDataset (CTD).
Alternatively, you can use one of the pre-generated CTDs we provide
via the package
ewceData
(which comes withEWCE
). - Run cell type enrichment on a user-provided gene list.
EWCE>=###
requires R>=4.1
and
Bioconductor>=1.4
. To install EWCE on Bioconductor run:
if (!require("BiocManager")){install.packages("BiocManager")}
BiocManager::install(version = "devel")
BiocManager::install("EWCE")
A minimal example to get started with running EWCE.
Example EWCE enrichment tests with in-depth explanations of each step.
Instructions on how to create new make new CellTypeDataset references to use with EWCE.
Examples and explanations of conditional cell type enrichment tests (e.g. controlling for a dominant cell type signal) .
Additional applications of EWCE to transcriptomic studies.
Docker containers with the latest version of
EWCE
are regularly pushed to Dockerhub. If
you already have Docker installed, you can load up a working copy using
the following commands.
Note, that you will need to replace the initial directory path with a location on your computer that you wish to be able to access from within the docker image.
docker pull nathanskene/ewce
docker run --name=ewce -e PASSWORD=ewcedocker -p 8790:8790 -d -v /User/$USER:/var/ewce nathanskene/ewce:latest
docker exec -ti ewce R
If you have any problems, please do submit an issue here on GitHub with a reproducible example.
If you use EWCE, please cite:
If you use the cortex/hippocampus single-cell data associated
EWCE
/ewceData
this package then please cite the following:
utils::sessionInfo()
## R version 4.1.1 (2021-08-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
##
## Matrix products: default
## BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=C
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## loaded via a namespace (and not attached):
## [1] compiler_4.1.1 magrittr_2.0.1 fastmap_1.1.0 tools_4.1.1
## [5] htmltools_0.5.2 yaml_2.2.1 stringi_1.7.5 rmarkdown_2.11
## [9] knitr_1.36 stringr_1.4.0 xfun_0.27 digest_0.6.28
## [13] rlang_0.4.12 evaluate_0.14
1. Skene, N. & Grant, S. Identification of vulnerable cell types in major brain disorders using single cell transcriptomes and expression weighted cell type enrichment. Frontiers in Neuroscience (2016). doi:10.3389/fnins.2016.00016