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Empowering Multi-Cohort Gene Expression Analysis to Increase Reproducibility

Winston A. Haynes, Francesco Vallania, Charles Liu, Erika Bongen, Aurelie Tomczak, Marta Andres-Terrè, Shane Lofgren, Andrew Tam, Cole A. Deisseroth, Matthew D. Li, Timothy E. Sweeney, Purvesh Khatri
doi: https://doi.org/10.1101/071514
Winston A. Haynes
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
2Biomedical Informatics Training Program, Stanford University, Stanford, California, USA
3Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
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Francesco Vallania
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Charles Liu
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
4Stanford Institutes of Medicine Research Program, Stanford University, Stanford, California, USA
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Erika Bongen
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
5Stanford Immunology, Stanford University, Stanford, California, USA
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Aurelie Tomczak
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
3Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
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Marta Andres-Terrè
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
5Stanford Immunology, Stanford University, Stanford, California, USA
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Shane Lofgren
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Andrew Tam
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Cole A. Deisseroth
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
4Stanford Institutes of Medicine Research Program, Stanford University, Stanford, California, USA
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Matthew D. Li
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
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Timothy E. Sweeney
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
3Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
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Purvesh Khatri
1Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA
3Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
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  • For correspondence: pkhatri@stanford.edu
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Abstract

A major contributor to the scientific reproducibility crisis has been that the results from homogeneous, single-center studies do not generalize to heterogeneous, real world populations. Multi-cohort gene expression analysis has helped to increase reproducibility by aggregating data from diverse populations into a single analysis. To make the multi-cohort analysis process more feasible, we have assembled an analysis pipeline which implements rigorously studied meta-analysis best practices. We have compiled and made publicly available the results of our own multi-cohort gene expression analysis of 103 diseases, spanning 615 studies and 36,915 samples, through a novel and interactive web application. As a result, we have made both the process of and the results from multi-cohort gene expression analysis more approachable for non-technical users.

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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. It is made available under a CC-BY 4.0 International license.
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Posted August 25, 2016.
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Empowering Multi-Cohort Gene Expression Analysis to Increase Reproducibility
Winston A. Haynes, Francesco Vallania, Charles Liu, Erika Bongen, Aurelie Tomczak, Marta Andres-Terrè, Shane Lofgren, Andrew Tam, Cole A. Deisseroth, Matthew D. Li, Timothy E. Sweeney, Purvesh Khatri
bioRxiv 071514; doi: https://doi.org/10.1101/071514
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Empowering Multi-Cohort Gene Expression Analysis to Increase Reproducibility
Winston A. Haynes, Francesco Vallania, Charles Liu, Erika Bongen, Aurelie Tomczak, Marta Andres-Terrè, Shane Lofgren, Andrew Tam, Cole A. Deisseroth, Matthew D. Li, Timothy E. Sweeney, Purvesh Khatri
bioRxiv 071514; doi: https://doi.org/10.1101/071514

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