ovarian cancer treatment resistance single-cell RNAseq analysis pipeline in Julia
This repository contains code used in the analysis of single-cell RNA sequencing. These codes are written in Julia (tested on versions 1.9.3) and are presented in Jupyter Notebook. Code blocks within the Jupyter Notebook are intended to be run independently.
- Julia (version 1.9.3)
- Jupyter Notebook
- DataFrames.jl
- CSV.jl
- StatsPlots.jl
- Statistics.jl
- StatsBase.jl
- Plots.jl
- Makie.jl
- IJulia.jl
- LinearAlgebra.jl
- MultivariateStats.jl
- MultipleTesting.jl
- NearestNeighbors.jl
- RCall.jl
- PyCall.jl
- SparseArrays.jl
- SCTransform.jl
- UMAP.jl
- TSne.jl
- PlotlyJS.jl
- MatrixMarket.jl
- Distances.jl
- CairoMakie.jl
- HypothesisTests.jl
- Leiden.jl
- CellScopes.jl
- AutomaticSingleCellToolbox.jl
- SingleCellProjections.jl
README.md: this file with information about the repository.A2780_ASCT.ipynb: using AutomaticSingleCellToolbox.jl to run scRNA-seq analysis.A2780_CellScopes.ipynb: using CellScopes.jl to run scRNAseq but it doesn't execute atscale_objectfunction.A2780_SingleCellProjections.ipynb: using SingleCellProjections.jl to run scRNA-seq analysis but it doesn't have clustering function.A2780: a folder of A2780 raw data.Data: raw data with genes and cells names and metadata stored in csv and raw data stored in h5.
We would like to thank Meghan C. Ferrall-Fairbanks and Adriana Del Pino Herrera for support and guidance.