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Characterizing blood modular transcriptional repertoire perturbations in patients with RSV infection: a hands-on workshop using public datasets as a source of training material

Darawan Rinchai, Oceane Konza, Signe Hassler, Federica Martina, Asuncion Mejias, Octavio Ramilo, Davide Bedognetti, Encarnita Mariotti-Ferrandiz, David Klatzmann, Damien Chaussabel
doi: https://doi.org/10.1101/527812
Darawan Rinchai
Sidra Medicine, Doha, Qatar;
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Oceane Konza
Inflammation-Immunopathology-Biotherapy Department (i2B), AP-HP, Pitie-Salpetriere Hospital, Paris;
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Signe Hassler
Inflammation-Immunopathology-Biotherapy Department (i2B), AP-HP, Pitie-Salpetriere Hospital, Paris;
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Federica Martina
Inflammation-Immunopathology-Biotherapy Department (i2B), AP-HP, Pitie-Salpetriere Hospital, Paris;
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Asuncion Mejias
Division of Infectious Diseases, Nationwide Children's Hospital, Columbus, OH, United States
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Octavio Ramilo
Division of Infectious Diseases, Nationwide Children's Hospital, Columbus, OH, United States
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Davide Bedognetti
Sidra Medicine, Doha, Qatar;
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Encarnita Mariotti-Ferrandiz
Inflammation-Immunopathology-Biotherapy Department (i2B), AP-HP, Pitie-Salpetriere Hospital, Paris;
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David Klatzmann
Inflammation-Immunopathology-Biotherapy Department (i2B), AP-HP, Pitie-Salpetriere Hospital, Paris;
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Damien Chaussabel
Sidra Medicine, Doha, Qatar;
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  • For correspondence: dchaussabel@sidra.org
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Abstract

Availability of large collections of public omics data creates a wide range of hands-on training opportunities for biomedical investigators. The organization and outcome of a workshop focusing on implementation of modular repertoire analysis and visualization approaches is described here. This analytic strategy has been developed specifically for mining of blood transcriptome data. Workshop participants conducted modular repertoire analyses of public blood transcriptome datasets generated from patients with acute respiratory syncytial virus infection (RSV). Analyses were conducted using a recently described 382-module repertoire framework. Next, group-level, as well as individual-level modular fingerprint plots, were generated. A meta-analysis encompassing 490 subjects was also conducted at the module-level by combining outputs from analyses of six independent datasets. Clustering was used to identify distinct patient subgroups in this consolidated patient cohort.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 22, 2019.
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Characterizing blood modular transcriptional repertoire perturbations in patients with RSV infection: a hands-on workshop using public datasets as a source of training material
Darawan Rinchai, Oceane Konza, Signe Hassler, Federica Martina, Asuncion Mejias, Octavio Ramilo, Davide Bedognetti, Encarnita Mariotti-Ferrandiz, David Klatzmann, Damien Chaussabel
bioRxiv 527812; doi: https://doi.org/10.1101/527812
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Characterizing blood modular transcriptional repertoire perturbations in patients with RSV infection: a hands-on workshop using public datasets as a source of training material
Darawan Rinchai, Oceane Konza, Signe Hassler, Federica Martina, Asuncion Mejias, Octavio Ramilo, Davide Bedognetti, Encarnita Mariotti-Ferrandiz, David Klatzmann, Damien Chaussabel
bioRxiv 527812; doi: https://doi.org/10.1101/527812

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