- Analyzing single-cell data in Julia, like Seurat v4 in R.
- Automatically choosing parameters for each function to implement auto pipeline.
- Add some functions for simple visualization.
- Add help informations for functions.
- Data exchange to other tools.
- Add more advanced funtions for dimensinal reduction, pseudotime analysis etc.
- Large-scaling by Julia's performance/data structure optimization.
- Web-based app for single-cell beginners and wet-lab users.
For this version, We use a mutable struct for a single-cell data set. It stores UMI data as sparse array and barcodes/features as DataFrame. The struct also saves all transformed data, meta information and operation logs.
- AutomaticSingleCellToolbox.jl: Module entrance.
- DataObject.jl: Definition of the single-cell data struct.
- DataFetch.jl: Definition of the functions for single-cell data reading.
- QualityCheck.jl: Definition of the functions of QC filtering and visualization.
- DataPreprocess.jl: Definition of the functions of data preprocessing.
- Reductions.jl: Definition of the functions of PCA, tSNE, UMAP etc.
- Clustering.jl/ModularityClustering.jl/SNN.jl/Louvain.jl: Definition of the functions for clustering.
- DE.jl: Definition of the functions for marker genes identification.
- DataManipulation.jl: Definition of the functions for data manipulation.
- Harmony.jl: Reimplementation of harmony algorithm for data integration.
- Visualization.jl: Implementation of some functions for plotting.