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Microarray-Based RNA Profiling of Breast Cancer : Batch Effect Removal Improves Cross-Platform Consistency
Joint Authors
Sørensen, Kristina P.
Larsen, Martin J.
Tan, Qihua
Kruse, Torben A.
Thomassen, Mads
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Microarray is a powerful technique used extensively for gene expression analysis.
Different technologies are available, but lack of standardization makes it challenging to compare and integrate data.
Furthermore, batch-related biases within datasets are common but often not tackled.
We have analyzed the same 234 breast cancers on two different microarray platforms.
One dataset contained known batch-effects associated with the fabrication procedure used.
The aim was to assess the significance of correcting for systematic batch-effects when integrating data from different platforms.
We here demonstrate the importance of detecting batch-effects and how tools, such as ComBat, can be used to successfully overcome such systematic variations in order to unmask essential biological signals.
Batch adjustment was found to be particularly valuable in the detection of more delicate differences in gene expression.
Furthermore, our results show that prober adjustment is essential for integration of gene expression data obtained from multiple sources.
We show that high-variance genes are highly reproducibly expressed across platforms making them particularly well suited as biomarkers and for building gene signatures, exemplified by prediction of estrogen-receptor status and molecular subtypes.
In conclusion, the study emphasizes the importance of utilizing proper batch adjustment methods when integrating data across different batches and platforms.
American Psychological Association (APA)
Larsen, Martin J.& Thomassen, Mads& Tan, Qihua& Sørensen, Kristina P.& Kruse, Torben A.. 2014. Microarray-Based RNA Profiling of Breast Cancer : Batch Effect Removal Improves Cross-Platform Consistency. BioMed Research International،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-488349
Modern Language Association (MLA)
Larsen, Martin J.…[et al.]. Microarray-Based RNA Profiling of Breast Cancer : Batch Effect Removal Improves Cross-Platform Consistency. BioMed Research International No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-488349
American Medical Association (AMA)
Larsen, Martin J.& Thomassen, Mads& Tan, Qihua& Sørensen, Kristina P.& Kruse, Torben A.. Microarray-Based RNA Profiling of Breast Cancer : Batch Effect Removal Improves Cross-Platform Consistency. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-488349
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-488349