Abstract
Integrating results from diverse experiments is an essential process in our effort to understand the logic of complex systems, such as development, homeostasis and responses to the environment. With the advent of high-throughput methods-including genome-wide association (GWA) studies, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and RNA sequencing (RNA-seq)-acquisition of genome-scale data has never been easier. Epigenomics, transcriptomics, proteomics and genomics each provide an insightful, and yet one-dimensional, view of genome function; integrative analysis promises a unified, global view. However, the large amount of information and diverse technology platforms pose multiple challenges for data access and processing. This Review discusses emerging issues and strategies related to data integration in the era of next-generation genomics.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 476-486 |
| Number of pages | 11 |
| Journal | Nature Reviews Genetics |
| Volume | 11 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jun 1 2010 |
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ASJC Scopus subject areas
- Molecular Biology
- Genetics
- Genetics(clinical)
Cite this
Next-generation genomics : An integrative approach. / Hawkins, R. David; Hon, Gary C.; Ren, Bing.
In: Nature Reviews Genetics, Vol. 11, No. 7, 01.06.2010, p. 476-486.Research output: Contribution to journal › Review article
}
TY - JOUR
T1 - Next-generation genomics
T2 - An integrative approach
AU - Hawkins, R. David
AU - Hon, Gary C.
AU - Ren, Bing
PY - 2010/6/1
Y1 - 2010/6/1
N2 - Integrating results from diverse experiments is an essential process in our effort to understand the logic of complex systems, such as development, homeostasis and responses to the environment. With the advent of high-throughput methods-including genome-wide association (GWA) studies, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and RNA sequencing (RNA-seq)-acquisition of genome-scale data has never been easier. Epigenomics, transcriptomics, proteomics and genomics each provide an insightful, and yet one-dimensional, view of genome function; integrative analysis promises a unified, global view. However, the large amount of information and diverse technology platforms pose multiple challenges for data access and processing. This Review discusses emerging issues and strategies related to data integration in the era of next-generation genomics.
AB - Integrating results from diverse experiments is an essential process in our effort to understand the logic of complex systems, such as development, homeostasis and responses to the environment. With the advent of high-throughput methods-including genome-wide association (GWA) studies, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and RNA sequencing (RNA-seq)-acquisition of genome-scale data has never been easier. Epigenomics, transcriptomics, proteomics and genomics each provide an insightful, and yet one-dimensional, view of genome function; integrative analysis promises a unified, global view. However, the large amount of information and diverse technology platforms pose multiple challenges for data access and processing. This Review discusses emerging issues and strategies related to data integration in the era of next-generation genomics.
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UR - http://www.scopus.com/inward/citedby.url?scp=77953808473&partnerID=8YFLogxK
U2 - 10.1038/nrg2795
DO - 10.1038/nrg2795
M3 - Review article
C2 - 20531367
AN - SCOPUS:77953808473
VL - 11
SP - 476
EP - 486
JO - Nature reviews. Genetics
JF - Nature reviews. Genetics
SN - 1471-0056
IS - 7
ER -