Research Topic

Big Data Analytics for Whole Exome Sequencing

About this Research Topic

Systems genomics in the form of next generation sequencing (NGS) has heralded a new direction. Today, one can study complex phenotypic traits measured using ‘omic’ technologies such as whole transcriptome/exome sequencing methods. While these technologies are applied to study genomes, transcriptomes, epigenomes or methylomes and link “exonic” variations in internal or external phenotypes, there has been an incessant need to put the big data into practice. Challenges on scaling data has paved the way for cloud and big data integration. On the other hand, there is a fallacy that modeling and systems-level analyses are still emerging in particular for whole exome sequencing (WES). In this Research Topic, we welcome authors involved in Big Data and NGS research to contribute submissions discussing sequencing challenges as seen through big data platforms. We welcome the submission of articles covering, but not limited to, the following topics:

1. Methods for analysing WES data in lieu of reduction in big data
2. Three Rs in practice: Does it apply for big data and NGS too?
3. Opportunities for big data in translational medicine.
4. Big data tools for trios and analysing exomes.
5. Big data in personalized medicine specific to WES.
6. Scalable sequence analyses comparing WES to other methods.

The Topic Editors would like to thank Dr. Garima and Dr. Vijayaraghava for their work in the preparation of this Research Topic.


Keywords: Big Data, Next Generation Sequencing, Exomes, Mapreduce, Variants


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Systems genomics in the form of next generation sequencing (NGS) has heralded a new direction. Today, one can study complex phenotypic traits measured using ‘omic’ technologies such as whole transcriptome/exome sequencing methods. While these technologies are applied to study genomes, transcriptomes, epigenomes or methylomes and link “exonic” variations in internal or external phenotypes, there has been an incessant need to put the big data into practice. Challenges on scaling data has paved the way for cloud and big data integration. On the other hand, there is a fallacy that modeling and systems-level analyses are still emerging in particular for whole exome sequencing (WES). In this Research Topic, we welcome authors involved in Big Data and NGS research to contribute submissions discussing sequencing challenges as seen through big data platforms. We welcome the submission of articles covering, but not limited to, the following topics:

1. Methods for analysing WES data in lieu of reduction in big data
2. Three Rs in practice: Does it apply for big data and NGS too?
3. Opportunities for big data in translational medicine.
4. Big data tools for trios and analysing exomes.
5. Big data in personalized medicine specific to WES.
6. Scalable sequence analyses comparing WES to other methods.

The Topic Editors would like to thank Dr. Garima and Dr. Vijayaraghava for their work in the preparation of this Research Topic.


Keywords: Big Data, Next Generation Sequencing, Exomes, Mapreduce, Variants


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

31 January 2018 Abstract
12 March 2018 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

31 January 2018 Abstract
12 March 2018 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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