curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome
| Autor: | Xin Victoria Wang, Benjamin Haibe-Kains, Giovanni Parmigiani, Benjamin Frederick Ganzfried, Ina Jazić, Thomas Risch, Curtis Huttenhower, Levi Waldron, Svitlana Tyekucheva, Mahnaz Ahmadifar, Michael J. Birrer, Markus Riester |
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| Rok vydání: | 2013 |
| Předmět: |
MEDLINE
Computational biology Biology computer.software_genre General Biochemistry Genetics and Molecular Biology Transcriptome Bioconductor 03 medical and health sciences 0302 clinical medicine Software Design Databases Genetic Data Mining Humans 030304 developmental biology Ovarian Neoplasms 0303 health sciences Microarray analysis techniques Clinical study design Chromosome Mapping Molecular Sequence Annotation Debulking Survival Analysis Chemokine CXCL12 3. Good health Biomarker (cell) Metadata Gene Expression Regulation Neoplastic 030220 oncology & carcinogenesis Female Original Article Data mining General Agricultural and Biological Sciences computer Information Systems |
| Zdroj: | Database: The Journal of Biological Databases and Curation |
| ISSN: | 1758-0463 |
| Popis: | 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. Database URL: http://bcb.dfci.harvard.edu/ovariancancer |
| Databáze: | OpenAIRE |
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