The Network Zoo: a multilingual package for the inference and analysis of biological networks

Author:

Guebila Marouen BenORCID,Wang TianORCID,Lopes-Ramos Camila M.ORCID,Fanfani ViolaORCID,Weighill DeborahORCID,Burkholz Rebekka,Schlauch DanielORCID,Paulson Joseph N.ORCID,Altenbuchinger MichaelORCID,Sonanwane Abhijeet,Lim James,Calderer Genis,van Ijzendoorn DavidORCID,Morgan DanielORCID,Marin AlessandroORCID,Chen Cho-YiORCID,Song Alex,Shutta KateORCID,DeMeo DawnORCID,Padi MeghaORCID,Platig John,Kuijjer Marieke L.ORCID,Glass KimberlyORCID,Quackenbush JohnORCID

Abstract

AbstractInference and analysis of cellular biological networks requires software tools that integrate multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is an open-source software suite to model biological networks, including context-specific gene regulatory networks and multi-omics partial correlation networks, to conduct differential analyses, estimate community structure, and model the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages (R, Python, MATLAB, and C) and between methods to allow a better integration of these tools into analytical pipelines. To demonstrate the value of this integrated toolkit, we analyzed the multi-omic data from the Cancer Cell Line Encyclopedia (CCLE) by inferring gene regulatory networks for each cancer cell line and associating network features with other phenotypic attributes such as drug sensitivity. This allowed us to identify transcription factors that play a critical role in both drug resistance and cancer development in melanoma. We also used netZoo to build a pan-cancer, multi-tiered CCLE map and used it to identify known metabolic hallmarks of cancer and to estimate novel context-specific elements that mediate post-transcriptional regulation. Because the netZoo tools are open-source and there is a growing community of both users and developers, we built an ecosystem to support community contributions, share use cases, and visualize networks online. As additional data types become available and our suite of methods grows, we will expand “the zoo” to incorporate an increasingly sophisticated collection of tools for network inference and analysis.

Publisher

Cold Spring Harbor Laboratory

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