Loading README.md +23 −1 Original line number Diff line number Diff line Loading @@ -5,4 +5,26 @@ DA-seq is a method to detect cell subpopulations with differential abundance bet This repository contains the DA-seq package. For more information, please visit our website for DAseq [here](https://klugerlab.github.io/DAseq). No newline at end of file ## R Dependencies Required packages: RANN, tclust, ggplot2, cowplot, RColorBrewer, scales, reticulate Suggested package: Seurat ## Python Dependencies Python 3 or above ([Miniconda](https://docs.conda.io/en/latest/miniconda.html) is recommended.) Required modules: numpy, pandas, sklearn, tensorflow, keras ## Installation The DAseq package can be installed from this GitHub repository. ~~~~ devtools::install_github("KlugerLab/DA-seq") ~~~~ ## Usage Please check DA-seq [tutorial](https://klugerlab.github.io/DAseq/pages/tutorial.html). Data used in the tutorial is from [Sade-Feldman, Moshe, et al. (Cell. 2018)](https://www.sciencedirect.com/science/article/pii/S0092867418313941). Loading
README.md +23 −1 Original line number Diff line number Diff line Loading @@ -5,4 +5,26 @@ DA-seq is a method to detect cell subpopulations with differential abundance bet This repository contains the DA-seq package. For more information, please visit our website for DAseq [here](https://klugerlab.github.io/DAseq). No newline at end of file ## R Dependencies Required packages: RANN, tclust, ggplot2, cowplot, RColorBrewer, scales, reticulate Suggested package: Seurat ## Python Dependencies Python 3 or above ([Miniconda](https://docs.conda.io/en/latest/miniconda.html) is recommended.) Required modules: numpy, pandas, sklearn, tensorflow, keras ## Installation The DAseq package can be installed from this GitHub repository. ~~~~ devtools::install_github("KlugerLab/DA-seq") ~~~~ ## Usage Please check DA-seq [tutorial](https://klugerlab.github.io/DAseq/pages/tutorial.html). Data used in the tutorial is from [Sade-Feldman, Moshe, et al. (Cell. 2018)](https://www.sciencedirect.com/science/article/pii/S0092867418313941).
