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A large-scale clinical study of gene expression response to severe burn injury

ABSTRACT: To understand the age-dependent response to burn injury, blood samples from pediatric and adult patients were collected at different times after severe burn injury. Gene expression was measured using Affymetrix U133 Plus 2.0 arrays for both patient samples and healthy controls. Time points were binned into two groups: early stage for <11 days and middle stage for 11-49 days. 114 arrays for 57 patients (2 time points per patient) and 63 arrays for 63 healthy controls.

ORGANISM(S): Homo sapiens

SUBMITTER: Weihong Xu 

PROVIDER: E-GEOD-19743 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

Zhou Baiyu B   Xu Weihong W   Herndon David D   Tompkins Ronald R   Davis Ronald R   Xiao Wenzhong W   Wong Wing Hung WH   Toner Mehmet M   Warren H Shaw HS   Schoenfeld David A DA   Rahme Laurence L   McDonald-Smith Grace P GP   Hayden Douglas D   Mason Philip P   Fagan Shawn S   Yu Yong-Ming YM   Cobb J Perren JP   Remick Daniel G DG   Mannick John A JA   Lederer James A JA   Gamelli Richard L RL   Silver Geoffrey M GM   West Michael A MA   Shapiro Michael B MB   Smith Richard R   Camp David G DG   Qian Weijun W   Storey John J   Mindrinos Michael M   Tibshirani Rob R   Lowry Stephen S   Calvano Steven S   Chaudry Irshad I   West Michael A MA   Cohen Mitchell M   Moore Ernest E EE   Johnson Jeffrey J   Moldawer Lyle L LL   Baker Henry V HV   Efron Philip A PA   Balis Ulysses G J UG   Billiar Timothy R TR   Ochoa Juan B JB   Sperry Jason L JL   Miller-Graziano Carol L CL   De Asit K AK   Bankey Paul E PE   Finnerty Celeste C CC   Jeschke Marc G MG   Minei Joseph P JP   Arnoldo Brett D BD   Hunt John L JL   Horton Jureta J   Cobb J Perren JP   Brownstein Bernard B   Freeman Bradley B   Maier Ronald V RV   Nathens Avery B AB   Cuschieri Joseph J   Gibran Nicole N   Klein Matthew M   O'Keefe Grant G  

Proceedings of the National Academy of Sciences of the United States of America 20100517 22

Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testin  ...[more]

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