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Cloud Computing for Next-Generation Sequencing Data Analysis

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High-throughput next-generation sequencing (NGS) technologies have evolved rapidly and are reshaping the scope of genomics research. The substantial decrease in the cost of NGS techniques in the past decade has led to its rapid adoption in biological research and drug development. Genomics studies of large populations are producing a huge amount of data, giving rise to computational issues around the storage, transfer, and analysis of the data. Fortunately, cloud computing has recently emerged as a viable option to quickly and easily acquire the computational resources for large-scale NGS data analyses. Some cloud-based applications and resources have been developed specifically to address the computational challenges of working with very large volumes of data generated by NGS technology. In this chapter, we will review some cloud-based systems and solutions for NGS data analysis, discuss the practical hurdles and limitations in cloud computing, including data transfer and security, and share the lessons we learned from the implementation of Rainbow, a cloud-based tool for large-scale genome sequencing data analysis.

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Detail Information

Series Title

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Call Number

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Publisher

: ., 2017

Collation

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Language

English

ISBN/ISSN

9789535132431

Classification

NONE

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Computers / Distributed Systems / Cloud Computing

Specific Detail Info

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Statement of Responsibility

ZHAO, Shanrong

Other Information

Cataloger

Suwardi

Source

https://openresearchlibrary.org/content/cdcb1f71-7bba-4ba6-9372-57d5e36a1871

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