Genome Biology (Mar 2023)
The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks
- Marouen Ben Guebila,
- Tian Wang,
- Camila M. Lopes-Ramos,
- Viola Fanfani,
- Des Weighill,
- Rebekka Burkholz,
- Daniel Schlauch,
- Joseph N. Paulson,
- Michael Altenbuchinger,
- Katherine H. Shutta,
- Abhijeet R. Sonawane,
- James Lim,
- Genis Calderer,
- David G.P. van IJzendoorn,
- Daniel Morgan,
- Alessandro Marin,
- Cho-Yi Chen,
- Qi Song,
- Enakshi Saha,
- Dawn L. DeMeo,
- Megha Padi,
- John Platig,
- Marieke L. Kuijjer,
- Kimberly Glass,
- John Quackenbush
Affiliations
- Marouen Ben Guebila
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Tian Wang
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Camila M. Lopes-Ramos
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Viola Fanfani
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Des Weighill
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Rebekka Burkholz
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Daniel Schlauch
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Joseph N. Paulson
- Department of Biochemistry and Molecular Biology, Pennsylvania State University College of Medicine
- Michael Altenbuchinger
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Katherine H. Shutta
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Abhijeet R. Sonawane
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School
- James Lim
- Department of Molecular and Cellular Biology, University of Arizona
- Genis Calderer
- Center for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo
- David G.P. van IJzendoorn
- Department of Pathology, Leiden University Medical Center
- Daniel Morgan
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School
- Alessandro Marin
- Expert Analytics AS
- Cho-Yi Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Qi Song
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School
- Enakshi Saha
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Dawn L. DeMeo
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School
- Megha Padi
- Department of Molecular and Cellular Biology, University of Arizona
- John Platig
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School
- Marieke L. Kuijjer
- Center for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo
- Kimberly Glass
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- John Quackenbush
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- DOI
- https://doi.org/10.1186/s13059-023-02877-1
- Journal volume & issue
-
Vol. 24,
no. 1
pp. 1 – 23
Abstract
Abstract Inference and analysis of gene regulatory networks (GRNs) require software that integrates multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is a collection of open-source methods to infer GRNs, conduct differential network analyses, estimate community structure, and explore the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages and between methods to allow better integration of these tools into analytical pipelines. We demonstrate the utility using multi-omic data from the Cancer Cell Line Encyclopedia. We will continue to expand the netZoo to incorporate additional methods.
Keywords
