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61. Testing for treatment effects on gene ontology

Author

Delongchamp Robert R, Reis Robert, Velasco Cruz, Desai Varsha G, and Lee Taewon

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract In studies that use DNA arrays to assess changes in gene expression, it is preferable to measure the significance of treatment effects on a group of genes from a pathway or functional category such as gene ontology terms (GO terms, http://www.geneontology.org) because this facilitates the interpretation of effects and may markedly increase significance. A modified meta-analysis method to combine p-values was developed to measure the significance of an overall treatment effect on such functionally-defined groups of genes, taking into account the correlation structure among genes. For hypothesis testing that allows gene expression to change in both directions, p-values are calculated under the null distribution generated by a Monte Carlo method. As a test of this procedure, we attempted to distinguish altered pathways in microarray studies performed with Mitochips, oligonucleotide microarrays specific to mitochondrial DNA-encoded transcripts. We found that our analytic method improves the specificity of selection for altered pathways, due to incorporation of the inter-gene correlation structure in each pathway. It is thus a practical method to measure treatment effects on GO groups. In many actual applications, microarray experiments measure treatment effects under complicated design structures and with small sample sizes. For such applications to real data of limited statistical power, and also in computer simulations, we demonstrate that our method gives reasonable test results.

Published
2008
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64. A method for computing the overall statistical significance of a treatment effect among a group of genes

Author

Delongchamp Robert, Lee Taewon, and Velasco Cruz

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background In studies that use DNA arrays to assess changes in gene expression, our goal is to evaluate the statistical significance of treatments on sets of genes. Genes can be grouped by a molecular function, a biological process, or a cellular component, e.g., gene ontology (GO) terms. The meaning of an affected GO group is often clearer than interpretations arising from a list of the statistically significant genes. Results Computer simulations demonstrated that correlations among genes invalidate many statistical methods that are commonly used to assign significance to GO terms. Ignoring these correlations overstates the statistical significance. Meta-analysis methods for combining p-values were modified to adjust for correlation. One of these methods is elaborated in the context of a comparison between two treatments. The form of the correlation adjustment depends upon the alternative hypothesis. Conclusion Reliable corrections for the effect of correlations among genes on the significance level of a GO term can be constructed for an alternative hypothesis where all transcripts in the GO term increase (decrease) in response to treatment. For general alternatives, which allow some transcripts to increase and others to decrease, the bias of naïve significance calculations can be greatly decreased although not eliminated.

Published
2006
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66. Del-1, an Endogenous Inhibitor of TGF-β Activation, Attenuates Fibrosis

Author

Kim, Dong-Young, primary, Lee, Seung-Hwan, additional, Fu, Yan, additional, Jing, Feifeng, additional, Kim, Won-Young, additional, Hong, Sang-Bum, additional, Song, Jung-A, additional, Choe, Han, additional, Ryu, Hyun Jin, additional, Kim, Minjung, additional, Lim, Dahae, additional, Kim, Min-Seon, additional, Yun, Chae-Ok, additional, Lee, Taewon, additional, Hyun, Hoon, additional, and Choi, Eun Young, additional

Published
2020
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87. Fully iterative scatter corrected digital breast tomosynthesis using GPU‐based fast Monte Carlo simulation and composition ratio update

Author

Kim, Kyungsang, primary, Lee, Taewon, additional, Seong, Younghun, additional, Lee, Jongha, additional, Jang, Kwang Eun, additional, Choi, Jaegu, additional, Choi, Young Wook, additional, Kim, Hak Hee, additional, Shin, Hee Jung, additional, Cha, Joo Hee, additional, Cho, Seungryong, additional, and Ye, Jong Chul, additional

Published
2015
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