Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework
Analysis of “omics” data is often a long and segmented process, encompassing multiple stages from initial data collection to processing, quality control and visualization. The cross-modal nature of recent genomic analyses renders this process challenging to both automate and standardize; consequentl...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-12-01
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| Series: | Frontiers in Neuroinformatics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fninf.2018.00091/full |
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Article |
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DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Samir Das Samir Das Xavier Lecours Boucher Xavier Lecours Boucher Christine Rogers Christine Rogers Carolina Makowski Carolina Makowski Carolina Makowski François Chouinard-Decorte François Chouinard-Decorte Kathleen Oros Klein Kathleen Oros Klein Natacha Beck Natacha Beck Pierre Rioux Pierre Rioux Shawn T. Brown Shawn T. Brown Zia Mohaddes Zia Mohaddes Cole Zweber Cole Zweber Victoria Foing Victoria Foing Marie Forest Marie Forest Kieran J. O’Donnell Kieran J. O’Donnell Joanne Clark Michael J. Meaney Michael J. Meaney Celia M. T. Greenwood Celia M. T. Greenwood Alan C. Evans Alan C. Evans |
| spellingShingle |
Samir Das Samir Das Xavier Lecours Boucher Xavier Lecours Boucher Christine Rogers Christine Rogers Carolina Makowski Carolina Makowski Carolina Makowski François Chouinard-Decorte François Chouinard-Decorte Kathleen Oros Klein Kathleen Oros Klein Natacha Beck Natacha Beck Pierre Rioux Pierre Rioux Shawn T. Brown Shawn T. Brown Zia Mohaddes Zia Mohaddes Cole Zweber Cole Zweber Victoria Foing Victoria Foing Marie Forest Marie Forest Kieran J. O’Donnell Kieran J. O’Donnell Joanne Clark Michael J. Meaney Michael J. Meaney Celia M. T. Greenwood Celia M. T. Greenwood Alan C. Evans Alan C. Evans Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework Frontiers in Neuroinformatics workflow omics analysis integrative neuroscience reproducibility database HPC |
| author_facet |
Samir Das Samir Das Xavier Lecours Boucher Xavier Lecours Boucher Christine Rogers Christine Rogers Carolina Makowski Carolina Makowski Carolina Makowski François Chouinard-Decorte François Chouinard-Decorte Kathleen Oros Klein Kathleen Oros Klein Natacha Beck Natacha Beck Pierre Rioux Pierre Rioux Shawn T. Brown Shawn T. Brown Zia Mohaddes Zia Mohaddes Cole Zweber Cole Zweber Victoria Foing Victoria Foing Marie Forest Marie Forest Kieran J. O’Donnell Kieran J. O’Donnell Joanne Clark Michael J. Meaney Michael J. Meaney Celia M. T. Greenwood Celia M. T. Greenwood Alan C. Evans Alan C. Evans |
| author_sort |
Samir Das |
| title |
Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework |
| title_short |
Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework |
| title_full |
Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework |
| title_fullStr |
Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework |
| title_full_unstemmed |
Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework |
| title_sort |
integration of “omics” data and phenotypic data within a unified extensible multimodal framework |
| publisher |
Frontiers Media S.A. |
| series |
Frontiers in Neuroinformatics |
| issn |
1662-5196 |
| publishDate |
2018-12-01 |
| description |
Analysis of “omics” data is often a long and segmented process, encompassing multiple stages from initial data collection to processing, quality control and visualization. The cross-modal nature of recent genomic analyses renders this process challenging to both automate and standardize; consequently, users often resort to manual interventions that compromise data reliability and reproducibility. This in turn can produce multiple versions of datasets across storage systems. As a result, scientists can lose significant time and resources trying to execute and monitor their analytical workflows and encounter difficulties sharing versioned data. In 2015, the Ludmer Centre for Neuroinformatics and Mental Health at McGill University brought together expertise from the Douglas Mental Health University Institute, the Lady Davis Institute and the Montreal Neurological Institute (MNI) to form a genetics/epigenetics working group. The objectives of this working group are to: (i) design an automated and seamless process for (epi)genetic data that consolidates heterogeneous datasets into the LORIS open-source data platform; (ii) streamline data analysis; (iii) integrate results with provenance information; and (iv) facilitate structured and versioned sharing of pipelines for optimized reproducibility using high-performance computing (HPC) environments via the CBRAIN processing portal. This article outlines the resulting generalizable “omics” framework and its benefits, specifically, the ability to: (i) integrate multiple types of biological and multi-modal datasets (imaging, clinical, demographics and behavioral); (ii) automate the process of launching analysis pipelines on HPC platforms; (iii) remove the bioinformatic barriers that are inherent to this process; (iv) ensure standardization and transparent sharing of processing pipelines to improve computational consistency; (v) store results in a queryable web interface; (vi) offer visualization tools to better view the data; and (vii) provide the mechanisms to ensure usability and reproducibility. This framework for workflows facilitates brain research discovery by reducing human error through automation of analysis pipelines and seamless linking of multimodal data, allowing investigators to focus on research instead of data handling. |
| topic |
workflow omics analysis integrative neuroscience reproducibility database HPC |
| url |
https://www.frontiersin.org/article/10.3389/fninf.2018.00091/full |
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doaj-684c4f7799bf45f0aad9a3ec40cf1f762020-11-24T21:45:41ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962018-12-011210.3389/fninf.2018.00091420191Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal FrameworkSamir Das0Samir Das1Xavier Lecours Boucher2Xavier Lecours Boucher3Christine Rogers4Christine Rogers5Carolina Makowski6Carolina Makowski7Carolina Makowski8François Chouinard-Decorte9François Chouinard-Decorte10Kathleen Oros Klein11Kathleen Oros Klein12Natacha Beck13Natacha Beck14Pierre Rioux15Pierre Rioux16Shawn T. Brown17Shawn T. Brown18Zia Mohaddes19Zia Mohaddes20Cole Zweber21Cole Zweber22Victoria Foing23Victoria Foing24Marie Forest25Marie Forest26Kieran J. O’Donnell27Kieran J. O’Donnell28Joanne Clark29Michael J. Meaney30Michael J. Meaney31Celia M. T. Greenwood32Celia M. T. Greenwood33Alan C. Evans34Alan C. Evans35McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaDouglas Hospital Research Centre, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaLudmer Centre for Neuroinformatics & Mental Health, McGill University, Montreal, QC, CanadaLady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaLudmer Centre for Neuroinformatics & Mental Health, McGill University, Montreal, QC, CanadaLady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, CanadaDouglas Hospital Research Centre, McGill University, Montreal, QC, CanadaLudmer Centre for Neuroinformatics & Mental Health, McGill University, Montreal, QC, CanadaLudmer Centre for Neuroinformatics & Mental Health, McGill University, Montreal, QC, CanadaDouglas Hospital Research Centre, McGill University, Montreal, QC, CanadaLudmer Centre for Neuroinformatics & Mental Health, McGill University, Montreal, QC, CanadaLudmer Centre for Neuroinformatics & Mental Health, McGill University, Montreal, QC, CanadaLady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, CanadaMcGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, QC, CanadaMontreal Neurological Institute, McGill University, Montreal, QC, CanadaAnalysis of “omics” data is often a long and segmented process, encompassing multiple stages from initial data collection to processing, quality control and visualization. The cross-modal nature of recent genomic analyses renders this process challenging to both automate and standardize; consequently, users often resort to manual interventions that compromise data reliability and reproducibility. This in turn can produce multiple versions of datasets across storage systems. As a result, scientists can lose significant time and resources trying to execute and monitor their analytical workflows and encounter difficulties sharing versioned data. In 2015, the Ludmer Centre for Neuroinformatics and Mental Health at McGill University brought together expertise from the Douglas Mental Health University Institute, the Lady Davis Institute and the Montreal Neurological Institute (MNI) to form a genetics/epigenetics working group. The objectives of this working group are to: (i) design an automated and seamless process for (epi)genetic data that consolidates heterogeneous datasets into the LORIS open-source data platform; (ii) streamline data analysis; (iii) integrate results with provenance information; and (iv) facilitate structured and versioned sharing of pipelines for optimized reproducibility using high-performance computing (HPC) environments via the CBRAIN processing portal. This article outlines the resulting generalizable “omics” framework and its benefits, specifically, the ability to: (i) integrate multiple types of biological and multi-modal datasets (imaging, clinical, demographics and behavioral); (ii) automate the process of launching analysis pipelines on HPC platforms; (iii) remove the bioinformatic barriers that are inherent to this process; (iv) ensure standardization and transparent sharing of processing pipelines to improve computational consistency; (v) store results in a queryable web interface; (vi) offer visualization tools to better view the data; and (vii) provide the mechanisms to ensure usability and reproducibility. This framework for workflows facilitates brain research discovery by reducing human error through automation of analysis pipelines and seamless linking of multimodal data, allowing investigators to focus on research instead of data handling.https://www.frontiersin.org/article/10.3389/fninf.2018.00091/fullworkflowomics analysisintegrative neurosciencereproducibilitydatabaseHPC |