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tigaR: integrative significance analysis of temporal differential gene expression induced by genomic abnormalities.

Miok V, Wilting SM, van de Wiel MA, Jaspers A, van Noort PI, Brakenhoff RH, Snijders PJ, Steenbergen RD, van Wieringen WN - BMC Bioinformatics (2014)

Bottom Line: In addition, to make estimates of the DNA copy number more stable, model parameters are also estimated in a multivariate way using triplets of features, imposing a spatial prior for the copy number effect.With the proposed method for analysis of time-course multilevel molecular data, more profound insight may be gained through the identification of temporal differential expression induced by DNA copy number abnormalities.Furthermore, the proposed method yields improvements in sensitivity, specificity and reproducibility compared to existing methods.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, VU University Medical Center, P,O, Box 7057, 1007 MB, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl.

ABSTRACT

Background: To determine which changes in the host cell genome are crucial for cervical carcinogenesis, a longitudinal in vitro model system of HPV-transformed keratinocytes was profiled in a genome-wide manner. Four cell lines affected with either HPV16 or HPV18 were assayed at 8 sequential time points for gene expression (mRNA) and gene copy number (DNA) using high-resolution microarrays. Available methods for temporal differential expression analysis are not designed for integrative genomic studies.

Results: Here, we present a method that allows for the identification of differential gene expression associated with DNA copy number changes over time. The temporal variation in gene expression is described by a generalized linear mixed model employing low-rank thin-plate splines. Model parameters are estimated with an empirical Bayes procedure, which exploits integrated nested Laplace approximation for fast computation. Iteratively, posteriors of hyperparameters and model parameters are estimated. The empirical Bayes procedure shrinks multiple dispersion-related parameters. Shrinkage leads to more stable estimates of the model parameters, better control of false positives and improvement of reproducibility. In addition, to make estimates of the DNA copy number more stable, model parameters are also estimated in a multivariate way using triplets of features, imposing a spatial prior for the copy number effect.

Conclusion: With the proposed method for analysis of time-course multilevel molecular data, more profound insight may be gained through the identification of temporal differential expression induced by DNA copy number abnormalities. In particular, in the analysis of an integrative oncogenomics study with a time-course set-up our method finds genes previously reported to be involved in cervical carcinogenesis. Furthermore, the proposed method yields improvements in sensitivity, specificity and reproducibility compared to existing methods. Finally, the proposed method is able to handle count (RNAseq) data from time course experiments as is shown on a real data set.

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Expression levels of SLC25A36 over time in a single cell line. The solid red and dashed blue lines are the fits of the model with and without DNA copy number parameter, respectively.
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Fig6: Expression levels of SLC25A36 over time in a single cell line. The solid red and dashed blue lines are the fits of the model with and without DNA copy number parameter, respectively.

Mentions: To contrast the results for CADM1, we focus on the SLC25A36 gene. SLC25A36 exhibits temporal differential expression (irrespective of the choice for common or different spline model). SLC25A36 is also identified as a gene with a significant DNA copy number effect with estimate . Inclusion of DNA copy number in the model improves the fit substantially (confer Figure 6, illustration on all four cell lines in Additional file 1, Section 7). This is seen in Figure 6 as the difference in fit for the model with and without DNA copy number. These results for SLC25A36 corroborate with existing medical literature: the gene dosage effect for this gene has already been reported in cervical cancer [31].Figure 6


tigaR: integrative significance analysis of temporal differential gene expression induced by genomic abnormalities.

Miok V, Wilting SM, van de Wiel MA, Jaspers A, van Noort PI, Brakenhoff RH, Snijders PJ, Steenbergen RD, van Wieringen WN - BMC Bioinformatics (2014)

Expression levels of SLC25A36 over time in a single cell line. The solid red and dashed blue lines are the fits of the model with and without DNA copy number parameter, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4288633&req=5

Fig6: Expression levels of SLC25A36 over time in a single cell line. The solid red and dashed blue lines are the fits of the model with and without DNA copy number parameter, respectively.
Mentions: To contrast the results for CADM1, we focus on the SLC25A36 gene. SLC25A36 exhibits temporal differential expression (irrespective of the choice for common or different spline model). SLC25A36 is also identified as a gene with a significant DNA copy number effect with estimate . Inclusion of DNA copy number in the model improves the fit substantially (confer Figure 6, illustration on all four cell lines in Additional file 1, Section 7). This is seen in Figure 6 as the difference in fit for the model with and without DNA copy number. These results for SLC25A36 corroborate with existing medical literature: the gene dosage effect for this gene has already been reported in cervical cancer [31].Figure 6

Bottom Line: In addition, to make estimates of the DNA copy number more stable, model parameters are also estimated in a multivariate way using triplets of features, imposing a spatial prior for the copy number effect.With the proposed method for analysis of time-course multilevel molecular data, more profound insight may be gained through the identification of temporal differential expression induced by DNA copy number abnormalities.Furthermore, the proposed method yields improvements in sensitivity, specificity and reproducibility compared to existing methods.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, VU University Medical Center, P,O, Box 7057, 1007 MB, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl.

ABSTRACT

Background: To determine which changes in the host cell genome are crucial for cervical carcinogenesis, a longitudinal in vitro model system of HPV-transformed keratinocytes was profiled in a genome-wide manner. Four cell lines affected with either HPV16 or HPV18 were assayed at 8 sequential time points for gene expression (mRNA) and gene copy number (DNA) using high-resolution microarrays. Available methods for temporal differential expression analysis are not designed for integrative genomic studies.

Results: Here, we present a method that allows for the identification of differential gene expression associated with DNA copy number changes over time. The temporal variation in gene expression is described by a generalized linear mixed model employing low-rank thin-plate splines. Model parameters are estimated with an empirical Bayes procedure, which exploits integrated nested Laplace approximation for fast computation. Iteratively, posteriors of hyperparameters and model parameters are estimated. The empirical Bayes procedure shrinks multiple dispersion-related parameters. Shrinkage leads to more stable estimates of the model parameters, better control of false positives and improvement of reproducibility. In addition, to make estimates of the DNA copy number more stable, model parameters are also estimated in a multivariate way using triplets of features, imposing a spatial prior for the copy number effect.

Conclusion: With the proposed method for analysis of time-course multilevel molecular data, more profound insight may be gained through the identification of temporal differential expression induced by DNA copy number abnormalities. In particular, in the analysis of an integrative oncogenomics study with a time-course set-up our method finds genes previously reported to be involved in cervical carcinogenesis. Furthermore, the proposed method yields improvements in sensitivity, specificity and reproducibility compared to existing methods. Finally, the proposed method is able to handle count (RNAseq) data from time course experiments as is shown on a real data set.

Show MeSH
Related in: MedlinePlus