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Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays.

ABSTRACT: Global analysis of gene expression by using DNA microarrays is employed increasingly to search for differences in biological properties between normal and diseased tissue. In such studies, expression that deviates from defined thresholds commonly is used for creating genetic signatures that characterize disease vs. normality. Although it is axiomatic that the threshold parameters applied to microarray analysis will alter the contents of such genetic signatures, the extent to which threshold choice can affect the fundamental conclusions made from microarray-based studies has not been elucidated. We used GABRIEL (Genetic Analysis By Rules Incorporating Expert Logic), a platform of knowledge-based algorithms for the global analysis of gene expression, together with conventional statistical approaches, to examine the sensitivity of conclusions to threshold choice in recently published microarray-based studies. An analysis of the effects of threshold decisions in one of these studies [Ramaswamy, S., Ross, K. N., Lander, E. S. & Golub, T. R. (2003) Nat. Genet. 33, 49-54], which arrived at the important conclusion that the metastatic potential of primary tumors is encoded by the bulk of cells in the tumor, is the focus of this article. We discovered that support for this conclusion highly depends on the threshold used to create gene expression signatures. We also found that threshold choice dramatically affected the gene function categories represented nonrandomly in signatures. Our results suggest that the robustness of biological conclusions made by using microarray analysis should be routinely assessed by examining the validity of the conclusions by using a range of threshold parameters.

SUBMITTER: Pan KH

PROVIDER: S-EPMC1149502 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesTo provide a participant's account of the development of a paper commissioned by the tobacco industry examining the reliability of self reported smoking status; to redress the distorted report of this Japanese spousal smoking study which evaluated the reliability and validity of self reported smoking status, and estimated confounding by diet and lifestyle factors.DesignRepeated interviews on smoking status and its verification by environmental and biological markers for environmental tobacco smoke (ETS) exposure.SettingUrban wives in Osaka City and Sizuoka City, JapanParticipantsSemi-random sampling of 200 wives in each city. From the Osaka subjects, 100 non-smoking wives were selected for the validity study.Main outcome measuresKappa coefficient for reliability of self reported smoking status. Correlation coefficients between environmental nicotine concentration, cotinine in saliva and urine, and self reported smoking status.ResultsThe kappa coefficient for the repeated interview was high suggesting sufficient reliability of the response. The proportion of self reported current smokers misclassified as non-smokers was equivalent to the misclassified self reported non-smokers. Ambient concentration of nicotine and personal exposure to nicotine correlated with each other and also with salivary cotinine and self reported ETS exposure but not with urinary cotinine/creatinine ratio (CCR). There was no major difference in diet and lifestyle related to husband's smoking status.ConclusionSelf reported smoking status by Japanese wives shows high reliability. It also shows high validity when verified by both nicotine exposure and salivary cotinine, but not by CCR. A previous report questioning the credibility of self reported smoking status, based on questionable CCR, could thus be of dubious validity. In addition, possible dietary and lifestyle confounding factors associated with smoking husbands were not demonstrable, a finding not reported previously. Using all the data from this project changes the conclusion of the previous published report. In addition to the distortion of scientific findings by a tobacco industry affiliated researcher, anti-smoking campaigners made attempts to intimidate and suppress scientific activities. These distortions of science should be counteracted.

Project description:BackgroundThe Saccharopolyspora erythraea genome sequence, recently published, presents considerable divergence from those of streptomycetes in gene organization and function, confirming the remarkable potential of S. erythraea for producing many other secondary metabolites in addition to erythromycin. In order to investigate, at whole transcriptome level, how S. erythraea genes are modulated, a DNA microarray was specifically designed and constructed on the S. erythraea strain NRRL 2338 genome sequence, and the expression profiles of 6494 ORFs were monitored during growth in complex liquid medium.ResultsThe transcriptional analysis identified a set of 404 genes, whose transcriptional signals vary during growth and characterize three distinct phases: a rapid growth until 32 h (Phase A); a growth slowdown until 52 h (Phase B); and another rapid growth phase from 56 h to 72 h (Phase C) before the cells enter the stationary phase. A non-parametric statistical method, that identifies chromosomal regions with transcriptional imbalances, determined regional organization of transcription along the chromosome, highlighting differences between core and non-core regions, and strand specific patterns of expression. Microarray data were used to characterize the temporal behaviour of major functional classes and of all the gene clusters for secondary metabolism. The results confirmed that the ery cluster is up-regulated during Phase A and identified six additional clusters (for terpenes and non-ribosomal peptides) that are clearly regulated in later phases.ConclusionThe use of a S. erythraea DNA microarray improved specificity and sensitivity of gene expression analysis, allowing a global and at the same time detailed picture of how S. erythraea genes are modulated. This work underlines the importance of using DNA microarrays, coupled with an exhaustive statistical and bioinformatic analysis of the results, to understand the transcriptional organization of the chromosomes of micro-organisms producing natural products.

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Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays.

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