Example usage using data from Human Protein Atlas and Bioplex

The cell maps pipeline requires the following input files for building MuSIC maps by integrating IF images with an AP-MS interaction network:

  1. samples file: CSV file with list of IF images to download (see sample samples file in examples folder)

  2. unique file: CSV file of unique samples (see sample unique file in examples folder)

  3. bait list file: TSV file of baits used for AP-MS experiments

  4. edge list file: TSV file of edges for protein interaction network

  5. provenance: file containing provenance information about input files in JSON format (see sample provenance file in examples folder, or create one directly as described above)

cellmaps_pipelinecmd.py ./cellmaps_pipeline_outdir --samples examples/samples.csv --unique examples/unique.csv \
                        --baitlist examples/baitlist.tsv --edgelist examples/edgelist.tsv \
                        --provenance examples/provenance.json

Each tool of the pipeline can be run separately in the following way:

# Download ImmunoFluorescent image data
cellmaps_imagedownloadercmd.py ./cellmaps_imagedownloader_outdir  --samples examples/samples.csv \
                               --unique examples/unique.csv --provenance examples/provenance.json

# Download Affinity-Purification mass spectrometry (AP-MS) data as a Protein-Protein Interaction network
cellmaps_ppidownloadercmd.py ./cellmaps_ppidownloader_outdir --edgelist examples/edgelist.tsv \
                             --baitlist examples/baitlist.tsv --provenance examples/provenance.json

# Generate embeddings from ImmunoFluorescent image data
cellmaps_image_embeddingcmd.py ./cellmaps_image_embedding_outdir --inputdir ./cellmaps_imagedownloader_outdir
                               --fold 1

# Generate embeddings from Protein-Protein interaction networks using node2vec
cellmaps_ppi_embeddingcmd.py ./cellmaps_ppi_embedding_outdir --inputdir ./cellmaps_ppidownloader_outdir

# Generate co-embedding from image and Protein-Protein Interaction (PPI) embeddings
cellmaps_coembeddingcmd.py ./cellmaps_coembedding_outdir --image_embeddingdir ./cellmaps_image_embedding_outdir \
                           --ppi_embeddingdir ./cellmaps_ppi_embedding_outdir

# Generate hierarchy from coembeddings using HiDeF.
cellmaps_generate_hierarchycmd.py ./cellmaps_generate_hierarchy_outdir --coembedding_dirs ./cellmaps_coembedding_outdir

# Annotate a hierarchy by performing enrichment against three NDEx networks HPA, CORUM, and GO-CC
cellmaps_hierarchyevalcmd.py ./cellmaps_hierarchyeval_outdir --hierarchy_dir ./cellmaps_generate_hierarchy_outdir

To run the pipeline programmatically, follow the steps detailed in the following notebook: A Step-By-Step Guide to Building Cellmaps Pipeline