TY - JOUR
T1 - curatedOvarianData
T2 - Clinically annotated data for the ovarian cancer transcriptome
AU - Ganzfried, Benjamin Frederick
AU - Riester, Markus
AU - Haibe-Kains, Benjamin
AU - Risch, Thomas
AU - Tyekucheva, Svitlana
AU - Jazic, Ina
AU - Wang, Xin Victoria
AU - Ahmadifar, Mahnaz
AU - Birrer, Michael J.
AU - Parmigiani, Giovanni
AU - Huttenhower, Curtis
AU - Waldron, Levi
PY - 2013
Y1 - 2013
N2 - This article introduces a manually curated data collection for gene expression meta-analysis of patients with ovarian cancer and software for reproducible preparation of similar databases. This resource provides uniformly prepared microarray data for 2970 patients from 23 studies with curated and documented clinical metadata. It allows users to efficiently identify studies and patient subgroups of interest for analysis and to perform meta-analysis immediately without the challenges posed by harmonizing heterogeneous microarray technologies, study designs, expression data processing methods and clinical data formats. We confirm that the recently proposed biomarker CXCL12 is associated with patient survival, independently of stage and optimal surgical debulking, which was possible only through meta-analysis owing to insufficient sample sizes of the individual studies. The database is implemented as the curatedOvarianData Bioconductor package for the R statistical computing language, providing a comprehensive and flexible resource for clinically oriented investigation of the ovarian cancer transcriptome. The package and pipeline for producing it are available from http://bcb.dfci.harvard.edu/ ovariancancer.
AB - This article introduces a manually curated data collection for gene expression meta-analysis of patients with ovarian cancer and software for reproducible preparation of similar databases. This resource provides uniformly prepared microarray data for 2970 patients from 23 studies with curated and documented clinical metadata. It allows users to efficiently identify studies and patient subgroups of interest for analysis and to perform meta-analysis immediately without the challenges posed by harmonizing heterogeneous microarray technologies, study designs, expression data processing methods and clinical data formats. We confirm that the recently proposed biomarker CXCL12 is associated with patient survival, independently of stage and optimal surgical debulking, which was possible only through meta-analysis owing to insufficient sample sizes of the individual studies. The database is implemented as the curatedOvarianData Bioconductor package for the R statistical computing language, providing a comprehensive and flexible resource for clinically oriented investigation of the ovarian cancer transcriptome. The package and pipeline for producing it are available from http://bcb.dfci.harvard.edu/ ovariancancer.
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U2 - 10.1093/database/bat013
DO - 10.1093/database/bat013
M3 - Article
C2 - 23550061
AN - SCOPUS:84879407005
SN - 1758-0463
VL - 2013
JO - Database
JF - Database
M1 - bat013
ER -