AlexsLemonade/OpenScPCA-analysis: v0.2.0

This release marks the first set of community-contributed analyses to the added to the repository. These modules are focused on cell type identification and annotation for specific ScPCA datasets. Note that many of these modules are still in development at this stage and may not be fully functional.

• cell-type-dsrct
• cell-type-ETP-ALL-03
• cell-type-glioblastoma
• cell-type-nonETP-ALL-03
• cell-type-wilms-tumor-06
• cell-type-wilms-tumor-14

This release also adds the following new modules developed by the Data Lab:

• cell-type-consensus: a module for exploring consensus cell types across multiple annotation methods
• hello-clusters: a demonstration module for clustering analysis using the rOpenScPCA package
• seurat-conversion: a module for converting SingleCellExperiment objects to Seurat objects, also using the rOpenScPCA package

Other updates in this release include:

• a new sync-results.py script to simplify uploading (and downloading) analysis results from an analysis module to a user's S3 bucket
• changes from miniconda to miniforge for conda usage throughout the project

While not part of this repository, we do want to also note that we have created the rOpenScPCA package, which will house utility functions commonly used by analysis modules here. The goal is to centralize common functions used across analysis modules to make it easier to share code and maintain consistency across modules.