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Omics Pipe: A Computational Framework for Reproducible Multi-Omics Data Analysis

View ORCID ProfileKathleen M. Fisch, View ORCID ProfileTobias Meissner, View ORCID ProfileLouis Gioia, View ORCID ProfileJean-Christophe Ducom, View ORCID ProfileTristan M. Carland, View ORCID ProfileSalvatore Loguercio, View ORCID ProfileAndrew I. Su
doi: https://doi.org/10.1101/008383
Kathleen M. Fisch
1Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, USA 92037
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  • ORCID record for Kathleen M. Fisch
Tobias Meissner
1Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, USA 92037
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Louis Gioia
1Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, USA 92037
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Jean-Christophe Ducom
3The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, USA 92037
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Tristan M. Carland
2Department of Human Biology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA, USA 92037
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Salvatore Loguercio
1Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, USA 92037
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Andrew I. Su
1Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, USA 92037
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Abstract

Omics Pipe (https://bitbucket.org/sulab/omics_pipe) is a computational platform that automates multi-omics data analysis pipelines on high performance compute clusters and in the cloud. It supports best practice published pipelines for RNA-seq, miRNA-seq, Exome-seq, Whole Genome sequencing, ChIP-seq analyses and automatic processing of data from The Cancer Genome Atlas. Omics Pipe provides researchers with a tool for reproducible, open source and extensible next generation sequencing analysis.

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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-NC-ND 4.0 International license.
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Posted August 23, 2014.
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Omics Pipe: A Computational Framework for Reproducible Multi-Omics Data Analysis
Kathleen M. Fisch, Tobias Meissner, Louis Gioia, Jean-Christophe Ducom, Tristan M. Carland, Salvatore Loguercio, Andrew I. Su
bioRxiv 008383; doi: https://doi.org/10.1101/008383
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Omics Pipe: A Computational Framework for Reproducible Multi-Omics Data Analysis
Kathleen M. Fisch, Tobias Meissner, Louis Gioia, Jean-Christophe Ducom, Tristan M. Carland, Salvatore Loguercio, Andrew I. Su
bioRxiv 008383; doi: https://doi.org/10.1101/008383

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