The real cost of sequencing: scaling computation to keep pace with data generation

As the cost of sequencing continues to decrease and the amount of sequence data generated grows, new paradigms for data storage and analysis are increasingly important. The relative scaling behavior of these evolving technologies will impact genomics research moving forward.

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Bibliographic Details
Published in:Genome Biology 2016-03, Vol.17 (1), p.53-53, Article 53
Main Authors: Muir, Paul, Li, Shantao, Lou, Shaoke, Wang, Daifeng, Spakowicz, Daniel J, Salichos, Leonidas, Zhang, Jing, Weinstock, George M, Isaacs, Farren, Rozowsky, Joel, Gerstein, Mark
Format: Article
Language:English
Subjects:
Algorithms
Archives & records
Biomedical Research
Cancer
Cloud computing
Computational Biology - methods
Computational Biology - trends
Data compression
Data processing
Datasets
Deoxyribonucleic acid
DNA
Error correction & detection
Funding
Genomes
Genomics
High-Throughput Nucleotide Sequencing - economics
High-Throughput Nucleotide Sequencing - methods
Humans
Information Storage and Retrieval
Opinion
Paradigms
Personal computers
Researchers
Scaling
Trends
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Description
Summary:As the cost of sequencing continues to decrease and the amount of sequence data generated grows, new paradigms for data storage and analysis are increasingly important. The relative scaling behavior of these evolving technologies will impact genomics research moving forward.
ISSN:1474-760X
1474-7596
1474-760X
DOI:10.1186/s13059-016-0917-0