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MetaNeighbor: a method to rapidly assess cell type identity using both functional and random gene sets ================ MetaNeighbor allows users to quantify cell type replicability across datasets using neighbor voting. Please refer to its [online](./ or [pdf]( documentation and consider citing [Crow et al (2018) Nature Communications]( if you find MetaNeighbor useful in your research. ## Quick installation procedure MetaNeighbor has been tested on Windows 10, MacOS Catalina 10.15 and Linux RHEL7 and is expected to run on reasonably up-to-date R (tested on versions 3.6 and 4.0). The main dependencies are the tidyverse, igraph and SingleCellExperiment libraries (full list can be found in [DESCRIPTION](./DESCRIPTION)), all missing dependencies will be automatically installed by running the following commands. To install the stable version of MetaNeighbor, we recommend using [Bioconductor]( ```{r} if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install() BiocManager::install("MetaNeighbor") ``` To install the development version of MetaNeighbor, we recommend installing the Github version: ```{r} if (!requireNamespace("devtools", quietly = TRUE)) install.packages("devtools") devtools::install_github("gillislab/MetaNeighbor") ``` Installation usually completes in 1 or 2 minutes, but can take up to 20 minutes if you are starting with an empty R distribution. ## MetaNeighbor demos To run a demo of MetaNeighbor, we recommend running the [vignette](./vignettes/MetaNeighbor.Rmd) used for the [documentation](./ or try one of our [protocols](