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

Thomas Karn; Achim Rody; Volkmar Müller; Marcus Schmidt; Sven Becker; Uwe Holtrich; Lajos Pusztai

doi:10.1016/j.gdata.2014.09.014

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

Thomas Karn
, Achim Rody
, Volkmar Müller
, Marcus Schmidt
, Sven Becker
, Uwe Holtrich
, Lajos Pusztai

Department of Gynecology and Obstetrics

Johann Wolfgang Goethe-University
University Hospital Hamburg-Eppendorf
Johannes Gutenberg University Mainz
Yale University

9 Citations (Scopus)

Abstract

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.

Original language	English
Journal	Genomics Data
Volume	2
Pages (from-to)	354-6
Number of pages	3
ISSN	2213-5960
DOIs	https://doi.org/10.1016/j.gdata.2014.09.014
Publication status	Published - 2014

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10.1016/j.gdata.2014.09.014

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title = "Control of dataset bias in combined Affymetrix cohorts of triple negative breast cancer",

abstract = "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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T1 - Control of dataset bias in combined Affymetrix cohorts of triple negative breast cancer

AU - Karn, Thomas

AU - Rody, Achim

AU - Müller, Volkmar

AU - Schmidt, Marcus

AU - Becker, Sven

AU - Holtrich, Uwe

AU - Pusztai, Lajos

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

U2 - 10.1016/j.gdata.2014.09.014

DO - 10.1016/j.gdata.2014.09.014

M3 - Journal articles

C2 - 26484129

SN - 2213-5960

VL - 2

SP - 354

EP - 356

JO - Genomics Data

JF - Genomics Data

ER -

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

Abstract

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