To cite the curatedOvarianData package in publications use:

Benjamin Frederick Ganzfried, Markus Riester, Benjamin Haibe-Kains, Thomas Risch, Svitlana Tyekucheva, Ina Jazic, Xin Victoria Wang, Mahnaz Ahmadifar, Michael Birrer, Giovanni Parmigiani, Curtis Huttenhower, Levi Waldron. curatedOvarianData: Clinically Annotated Data for the Ovarian Cancer Transcriptome, Database 2013: bat013<doi:10.1093/database/bat013> published online April 2, 2013.

Corresponding BibTeX entry:

  @Article{,
    title = {curatedOvarianData: Clinically Annotated Data for the
      Ovarian Cancer Transcriptome},
    author = {Benjamin Frederick Ganzfried and Markus Riester and
      Benjamin Haibe-Kains and Thomas Risch and Svitlana Tyekucheva and
      Ina Jazic and Xin Victoria Wang and Mahnaz Ahmadifar and Michael
      Birrer and Giovanni Parmigiani and Curtis Huttenhower and Levi
      Waldron},
    volume = {2013},
    year = {2013},
    doi = {10.1093/database/bat013},
    abstract = {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},
    url =
      {http://database.oxfordjournals.org/content/2013/bat013.abstract},
    eprint =
      {http://database.oxfordjournals.org/content/2013/bat013.full.pdf+html},
    journal = {Database},
  }