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An online notebook resource for reproducible inference, analysis and publication of gene regulatory networks

Nature Methods volume 19, pages 511–513 (2022)Cite this article

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To the Editor — Open access to software in computational and systems biology, including data, code and models, is widely acknowledged as essential for ensuring reproducibility of research results and reuse of methods1. Although there are software tools that allow sharing of computational pipelines, these systems generally do not allow the integration of software annotation and documentation at each step in the process — elements that are required to understand and run complex and rapidly evolving software, including methods developed in systems biology for inferring biological pathways.

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Fig. 1: Netbooks contains a catalog of 19 case studies in regulatory genomics using the Network Zoo tools.

Code availability

Netbooks can be accessed through http://netbooks.networkmedicine.org and the individual Jupyter notebooks are available at https://github.com/netZoo/netbooks.

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Acknowledgements

M.L.K. and R.T.P. are supported by grants from the Norwegian Research Council (313932) and the Norwegian Cancer Society (214871). M.L.K. is also supported by the Norwegian Research Council, Helse Sør-Øst and University of Oslo through the Centre for Molecular Medicine Norway (187615). K.G. is supported by a grant from the US National Heart, Lung, and Blood Institute, National Institutes of Health, K25HL133599. J.P. is supported by US National Heart, Lung, and Blood Institute grant K25HL140186. C.M.L.-R., R.B., D.W., M.B.G. and J.Q. are supported by a grant from the National Cancer Institute, National Institutes of Health, R35CA220523; J.Q. and M.B.G. are also supported by U24CA231846; J.Q. is supported by additional grants from the US National Institutes of Health, 2P50CA127003, 5R01CA205406 and 5R01HL135142. C.M.L.-R. is also supported by a grant from the American Lung Association, LCD-821824 and by the National Heart, Lung, and Blood Institute, 5T32HL007427-41. M.F. is supported by a Marie Sklodowska-Curie grant (PATTERNS 845083). M.A. is supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (grant no. 01ZX1912C).

Author information

Author notes

  1. Deborah Weighill

    Present address: UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

  2. Rebekka Burkholz

    Present address: CISPA Helmholtz Center for Information Security, Saarbrücken, Germany

  3. These authors contributed equally: Marouen Ben Guebila, Deborah Weighill.

Authors and Affiliations

  1. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Marouen Ben Guebila, Deborah Weighill, Camila M. Lopes-Ramos, Rebekka Burkholz, Maud Fagny, Daniel Schlauch, Kimberly Glass & John Quackenbush

  2. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

    Camila M. Lopes-Ramos, Kimberly Glass, John Platig & John Quackenbush

  3. Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, Oslo, Norway

    Romana T. Pop & Marieke L. Kuijjer

  4. Harvard University, Cambridge, MA, USA

    Kalyan Palepu

  5. Boston University Academy, Boston, MA, USA

    Mia Shapoval

  6. Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE – Le Moulon, Gif-sur-Yvette, France

    Maud Fagny

  7. Genospace, Boston, MA, USA

    Daniel Schlauch

  8. Institute of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany

    Michael Altenbuchinger

  9. Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands

    Marieke L. Kuijjer

  10. Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, the Netherlands

    Marieke L. Kuijjer

  11. Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA

    John Quackenbush

Authors
  1. Marouen Ben Guebila
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  2. Deborah Weighill
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  10. Kimberly Glass
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  13. John Platig
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  14. John Quackenbush
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Contributions

M.B.G. and J.Q conceived the project. D.W., C.M.L.-R, R.B., R.T.P., K.P., M.S., M.F., D.S., K.G., M.A., M.L.K. and J.P. contributed use cases for the collection of notebooks. All authors edited and approved the final manuscript.

Corresponding author

Correspondence to John Quackenbush.

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The authors declare no competing interests.

Peer review

Peer review information

Nature Methods thanks Laurence Calzone and Michael Reich for their contribution to the peer review of this work.

Supplementary Information

Supplementary Information

Supplementary Note 1 and Table 1

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Ben Guebila, M., Weighill, D., Lopes-Ramos, C.M. et al. An online notebook resource for reproducible inference, analysis and publication of gene regulatory networks. Nat Methods 19, 511–513 (2022). https://doi.org/10.1038/s41592-022-01479-2

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