dorsal/arxiv
View SchemaDoes Logarithm Transformation of Microarray Data Affect Ranking Order of Differentially Expressed Genes?
| Authors | Wentian Li, Young Ju Suh, Jingshan Zhang |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0606018 |
| URL | https://arxiv.org/abs/q-bio/0606018 |
| DOI | 10.1109/IEMBS.2006.260896 |
Abstract
A common practice in microarray analysis is to transform the microarray raw data (light intensity) by a logarithmic transformation, and the justification for this transformation is to make the distribution more symmetric and Gaussian-like. Since this transformation is not universally practiced in all microarray analysis, we examined whether the discrepancy of this treatment of raw data affect the "high level" analysis result. In particular, whether the differentially expressed genes as obtained by $t$-test, regularized t-test, or logistic regression have altered rank orders due to presence or absence of the transformation. We show that as much as 20%--40% of significant genes are "discordant" (significant only in one form of the data and not in both), depending on the test being used and the threshold value for claiming significance. The t-test is more likely to be affected by logarithmic transformation than logistic regression, and regularized $t$-test more affected than t-test. On the other hand, the very top ranking genes (e.g. up to top 20--50 genes, depending on the test) are not affected by the logarithmic transformation.
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"abstract": "A common practice in microarray analysis is to transform the microarray raw\ndata (light intensity) by a logarithmic transformation, and the justification\nfor this transformation is to make the distribution more symmetric and\nGaussian-like. Since this transformation is not universally practiced in all\nmicroarray analysis, we examined whether the discrepancy of this treatment of\nraw data affect the \"high level\" analysis result. In particular, whether the\ndifferentially expressed genes as obtained by $t$-test, regularized t-test, or\nlogistic regression have altered rank orders due to presence or absence of the\ntransformation. We show that as much as 20%--40% of significant genes are\n\"discordant\" (significant only in one form of the data and not in both),\ndepending on the test being used and the threshold value for claiming\nsignificance. The t-test is more likely to be affected by logarithmic\ntransformation than logistic regression, and regularized $t$-test more affected\nthan t-test. On the other hand, the very top ranking genes (e.g. up to top\n20--50 genes, depending on the test) are not affected by the logarithmic\ntransformation.",
"arxiv_id": "q-bio/0606018",
"authors": [
"Wentian Li",
"Young Ju Suh",
"Jingshan Zhang"
],
"categories": [
"q-bio.QM"
],
"doi": "10.1109/IEMBS.2006.260896",
"title": "Does Logarithm Transformation of Microarray Data Affect Ranking Order of Differentially Expressed Genes?",
"url": "https://arxiv.org/abs/q-bio/0606018"
},
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