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KMID : 1147120160220010029
Journal of the Korean Society of Imaging Informatics in Medicine
2016 Volume.22 No. 1 p.29 ~ p.37
Repeatability of Gene Set Enrichment Analysis in Radiogenomics
Woo Bo-Yeong

Lee Myung-Eun
Kim Jong-Hyo
Abstract
Purpose: Radiogenomics has drawn significant research attention recently. Gene Set Enrichment Analysis (GSEA) is currently one of the most widely adopted gene analysis methods in radiogenomics. However, some studies have raised questions about the repeatability of GSEA. In this regard, this paper introduces gene set analysis, discusses how gene set analysis might be used in radiogenomics, and assesses the repeatability of GSEA through a simple experiment.

Materials and Methods: For assessing the repeatability of GSEA, we used gene expression data of 30 glioblastoma multiforme (GBM) patients from The Cancer Genome Atlas (TCGA). The corresponding brain MR images were obtained from The Cancer Imaging Archive (TCIA). We measured the area and uniformity of enhancing lesion and the area of necrotic lesion from axial T1 post-contrast image, classified the samples into those with low values and those with high values, and carried out repeated analysis-5 times each-using GSEA.

Results: In our repeated analysis using GSEA for the area of enhancing lesion, the 5 results were all the same, but for the area of necrotic lesion, the results varied a little each time. And when we ran the experiment for the uniformity of enhancing lesion, we found the 5 results to be very different from each other. This was thought to be because the false discovery rate (FDR) q-value, which is used by GSEA to show statistical significance, came out different every time.

Conclusion: We have confirmed that the repeatability of GSEA may vary widely depending on image features. Nevertheless, gene set analysis has the potential for further improvement, and radiogenomics also is constantly improving, so we expect to see more radiogenomics researches utilizing gene set analysis come out in the upcoming years.
KEYWORD
Radiogenomics, Gene set analysis, GSEA, Reliability, Repeatability
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