Control of dataset bias in combined affymetrix cohorts of triple negative breast cancer

  • Heterogenous subtypes of breast cancer need to be analyzed separately. Pooling of datasets can provide reasonable sample sizes but dataset bias is an important concern. We assembled a combined dataset of 579 Affymetrix microarrays from triple negative breast cancer (TNBC) in Gene Expression Omnibus (GEO) series GSE31519. We developed a method for selecting comparable datasets and to control for the amount of dataset bias of individual probesets.

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Author:Thomas Karn, Achim Rody, Volkmar MüllerGND, Marcus Schmidt, Sven BeckerGND, Uwe Holtrich, Lajos Pusztai
URN:urn:nbn:de:hebis:30:3-442051
DOI:https://doi.org/10.1016/j.gdata.2014.09.014
ISSN:2213-5960
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/26484129
Parent Title (English):Genomics data
Publisher:Elsevier
Place of publication:Amsterdam [u. a.]
Document Type:Article
Language:English
Date of Publication (online):2017/06/12
Year of first Publication:2014
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2017/06/12
Tag:Breast cancer; Dataset bias; Gene expression; Microarray; Pooling
Volume:2
Page Number:3
First Page:354
Last Page:356
Note:
© 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
HeBIS-PPN:428607896
Institutes:Medizin / Medizin
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung 3.0