三阴性乳腺癌联合Affymetrix队列中数据集偏差的控制
Control of dataset bias in combined Affymetrix cohorts of triple negative breast cancer.
作者信息
Karn Thomas, Rody Achim, Müller Volkmar, Schmidt Marcus, Becker Sven, Holtrich Uwe, Pusztai Lajos
机构信息
Department of Gynecology, Goethe-University Frankfurt, Frankfurt am Main, Germany.
Department of Obstetrics and Gynecology, University Hospital Lübeck, Germany.
出版信息
Genom Data. 2014 Oct 23;2:354-6. doi: 10.1016/j.gdata.2014.09.014. eCollection 2014 Dec.
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.
乳腺癌的异质性亚型需要分别进行分析。数据集的合并可以提供合理的样本量，但数据集偏差是一个重要问题。我们从基因表达综合数据库（GEO）系列GSE31519中收集了579个三阴性乳腺癌（TNBC）的Affymetrix微阵列的组合数据集。我们开发了一种方法来选择可比数据集，并控制单个探针集的数据集偏差量。
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