Transcriptomics,Proteomics

Dataset Information

67

Integrated analysis of omics profiles


ABSTRACT: This SuperSeries is composed of the following subset Series: GSE32691: Autoantibody profile timecourse of UNK GSE32874: Personal Omics Profiling Reveals Dynamic Molecular Phenotypes and Actionable Medical Risks Refer to individual Series

ORGANISM(S): Homo sapiens  

SUBMITTER: Hogune Im  

PROVIDER: E-GEOD-33029 | ArrayExpress | 2012-03-16

SECONDARY ACCESSION(S): GSE33029PRJNA148005

REPOSITORIES: GEO, ArrayExpress

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Publications

Personal omics profiling reveals dynamic molecular and medical phenotypes.

Chen Rui R   Mias George I GI   Li-Pook-Than Jennifer J   Jiang Lihua L   Lam Hugo Y K HY   Chen Rong R   Miriami Elana E   Karczewski Konrad J KJ   Hariharan Manoj M   Dewey Frederick E FE   Cheng Yong Y   Clark Michael J MJ   Im Hogune H   Habegger Lukas L   Balasubramanian Suganthi S   O'Huallachain Maeve M   Dudley Joel T JT   Hillenmeyer Sara S   Haraksingh Rajini R   Sharon Donald D   Euskirchen Ghia G   Lacroute Phil P   Bettinger Keith K   Boyle Alan P AP   Kasowski Maya M   Grubert Fabian F   Seki Scott S   Garcia Marco M   Whirl-Carrillo Michelle M   Gallardo Mercedes M   Blasco Maria A MA   Greenberg Peter L PL   Snyder Phyllis P   Klein Teri E TE   Altman Russ B RB   Butte Atul J AJ   Ashley Euan A EA   Gerstein Mark M   Nadeau Kari C KC   Tang Hua H   Snyder Michael M  

Cell 20120301 6


Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes  ...[more]

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