- Setup your environment using one of the .yml files
- Make a data folder and download the Tangram sample data by running:
# MOp 10Xv3 dataset
wget https://storage.googleapis.com/tommaso-brain-data/tangram_demo/mop_sn_tutorial.h5ad.gz -O data/mop_sn_tutorial.h5ad.gz
# SlideSeq data
wget https://storage.googleapis.com/tommaso-brain-data/tangram_demo/slideseq_MOp_1217.h5ad.gz -O data/slideseq_MOp_1217.h5ad.gz
wget https://storage.googleapis.com/tommaso-brain-data/tangram_demo/MOp_markers.csv -O data/MOp_markers.csv
gunzip -f data/mop_sn_tutorial.h5ad.gz
gunzip -f data/slideseq_MOp_1217.h5ad.gz
# Smart-Seq2_VISp_snRNAseq
wget https://ftp.ncbi.nlm.nih.gov/geo/series/GSE115nnn/GSE115746/suppl/GSE115746_cells_exon_counts.csv.gz -O data/cells_exons_VISp.csv.gz
gunzip data/cells_exons_VISp.csv.gz
wget https://ftp.ncbi.nlm.nih.gov/geo/series/GSE115nnn/GSE115746/suppl/GSE115746_complete_metadata_28706-cells.csv.gz -O data/metadata.csv.gz
gunzip data/metadata.csv.gz
- For STARMAP download https://zenodo.org/record/3967291#.Yz7aAexBxJU and transfer the Spatial/Starmap/visual_1020/20180505_BY3_1kgenes/ folder to data
- Convert the Smart-Seq2 and STARMAP datasets to h5ad files with
convert_to_h5ad.py
- Run
obtain_tangram_ad_maps
to get all mappings - Run
obtain_tangram_expressions
to get all gene expression predictions - Run
process_results
to get the dataframes needed for visualization
- Download the CellTrek sample data from their Dropbox and put them into the data folder:
- Open R, write renv::restore(). If it asks you: Would you like to activate this project before restore? [Y/n], click Y and install all dependencies.
- Run
celltrek_runs.R
on a server to obtain the results - Follow
celltrek.Rmd
for visualization