A systematic comparison across pathway databases
Project description
The primary goal of this package is to convert KEGG, Reactome, and WikiPathways (see References below) to Biological Expression Language (BEL). PathMe is the continuation of the ComPath web application aimed at exploring, analyzing, and curating pathway knowledge in a more simplistic gene-centric view. This different approach involves converting all the pathways to BEL as a pivotal integration schema and evaluating consensus and gaps in pathway knowledge. Additionally, ComPath Reloaded is complemented with PathMe, a web application that enables the exploration of all the pathways from these resources using the mappings curated from ComPath.
Installation 
pathme can be installed with the following commmands:
python3 -m pip install git+https://github.com/ComPath/PathMe.git@masteror in editable mode with:
git clone https://github.com/ComPath/PathMe.gitcd pathmepython3 -m pip install -e .How to use
Each database has three main commands: “download”, “to_bel”, and “summarize”:
Download content
PathMe first requires to download the raw files from the original pathway databases. This can be accomplished by running the command (‘database’ can be either kegg, reactome, or wikipathways):
python3 -m pathme 'database' downloadGenerate BEL Graphs
Once the raw files are downloaded, you can run the following to command to generate BELGraphs that will be exported as Python pickles files for further analysis. Furthermore, the conversion to BEL can be tuned differently for each database by using specific commands. For example, KEGG parameters are shown when running “python3 -m pathme kegg to_bel –help”.
python3 -m pathme 'database' to_belSummarize
Summarizes the result of the conversion to BEL.
python3 -m pathme 'database' summarizeAdvance parameters
KEGG Functionalities
The KEGG module of PathMe is able to handle KGML differently depending on the goal. By default, KEGG groups together the complex of nodes (e.g., gene families) into one node as it is depicted in the KEGG cartoons and represented in the KGML files. However, this behavior can be modified by adding the parameter “–flatten=True” in the exporting command. Example:
python3 -m pathme kegg to_bel --flatten=TrueReferences
KEGG
PathMe makes use of KEGG KGML files that are downloaded via the KEGG API for academic purposes (see KEGG Terms and conditions.).
Kanehisa, Furumichi, M., Tanabe, M., Sato, Y., and Morishima, K.; KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353-D361 (2017).
Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M., and Tanabe, M.; KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457-D462 (2016).
Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27-30 (2000).
Reactome
Fabregat, Antonio et al. “The Reactome Pathway Knowledgebase.” Nucleic Acids Research 44.Database issue (2016): D481–D487. PMC. Web. 6 Oct. 2017.
Croft, David et al. “The Reactome Pathway Knowledgebase.” Nucleic Acids Research 42.Database issue (2014): D472–D477. PMC. Web. 6 Oct. 2017.
WikiPathways
Slenter, D.N., et al WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research Nucleic Acids Research, (2017) doi.org/10.1093/nar/gkx1064
Kutmon, M., et al. WikiPathways: capturing the full diversity of pathway knowledge Nucl. Acids Res., 44, D488-D494 (2016) doi:10.1093/nar/gkv1024
Kelder, T., et al. WikiPathways: building research communities on biological pathways. Nucleic Acids Res. 2012 Jan;40(Database issue):D1301-7
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