pathme 0.0.3

Harmonizing pathway databases using Biological Expression Language (BEL)

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 gene-centric view. This different approach involves converting all the pathways to BEL as a pivotal integration schema to evaluate pathway cross-talks and consensus across multiple databases. 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

1. pathme can be installed with the following commands:

python3 -m pip install git+https://github.com/ComPath/PathMe.git@master

2. or in editable mode with:

git clone https://github.com/ComPath/PathMe.git

cd pathme

python3 -m pip install -e .

How to use

Each database has three main commands: “download”, “bel”, and “summarize”:

1. 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' download

2. Generate 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 bel –help.

python3 -m pathme 'database' bel

2. Summarize

Summarizes the result of the conversion to BEL.

python3 -m pathme 'database' summarize

Advance 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 bel --flatten=True

References

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