A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

Mélina Gallopin; Andrea Rau; Florence Jaffrézic

doi:10.1371/journal.pone.0077503

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Open Access

Peer-reviewed

Research Article

A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

Mélina Gallopin ,

* E-mail: melina.gallopin@jouy.inra.fr

Affiliations Département de Génétique Animale, INRA, Jouy-en-Josas, France, Département de Génétique Animale, AgroParis Tech, Paris, France, Département de Mathématiques, Université Paris-Sud 11, Orsay, France
⨯
Andrea Rau,

Affiliations Département de Génétique Animale, INRA, Jouy-en-Josas, France, Département de Génétique Animale, AgroParis Tech, Paris, France
⨯
Florence Jaffrézic

Affiliations Département de Génétique Animale, INRA, Jouy-en-Josas, France, Département de Génétique Animale, AgroParis Tech, Paris, France
⨯

A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

Mélina Gallopin,
Andrea Rau,
Florence Jaffrézic

Published: October 17, 2013
https://doi.org/10.1371/journal.pone.0077503

About the Authors

Mélina Gallopin

* E-mail: melina.gallopin@jouy.inra.fr

Affiliations Département de Génétique Animale, INRA, Jouy-en-Josas, France, Département de Génétique Animale, AgroParis Tech, Paris, France, Département de Mathématiques, Université Paris-Sud 11, Orsay, France

Andrea Rau

Affiliations Département de Génétique Animale, INRA, Jouy-en-Josas, France, Département de Génétique Animale, AgroParis Tech, Paris, France

Florence Jaffrézic

Affiliations Département de Génétique Animale, INRA, Jouy-en-Josas, France, Département de Génétique Animale, AgroParis Tech, Paris, France

Competing Interests

The authors have declared that no competing interests exist.

Author Contributions

Conceived and designed the experiments: AR FJ. Performed the experiments: MG. Analyzed the data: MG. Contributed reagents/materials/analysis tools: MG AR FJ. Wrote the paper: MG AR FJ.

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MicroRNAs
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Gene expression
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Breast cancer
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Gene regulatory networks
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Random variables
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Genetic networks
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Network analysis
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