Statistical method for modeling sequencing data from different technologies in longitudinal studies with application to Huntington disease
Biometrical Journal, vol. 63, pp. 745–760
Abstract
Advancement of gene expression measurements in longitudinal studies enables the identification of genes associated with disease severity over time. However, problems arise when the technology used to measure gene expression differs between time points. Observed differences between the results obtained at different time points can be caused by technical differences. Modeling the two measurements jointly over time might provide insight into the causes of these different results. Our work is motivated by a study of gene expression data of blood samples from Huntington disease patients, which were obtained using two different sequencing technologies. At time point 1, DeepSAGE technology was used to measure the gene expression, with a subsample also measured using RNA-Seq technology. At time point 2, all samples were measured using RNA-Seq technology. Significant associations between gene expression measured by DeepSAGE and disease severity using data from the first time point could not be replicated by the RNA-Seq data from the second time point. We modeled the relationship between the two sequencing technologies using the data from the overlapping samples. We used linear mixed models with either DeepSAGE or RNA-Seq measurements as the dependent variable and disease severity as the independent variable. In conclusion, (1) for one out of 14 genes, the initial significant result could be replicated with both technologies using data from both time points; (2) statistical efficiency is lost due to disagreement between the two technologies, measurement error when predicting gene expressions, and the need to include additional parameters to account for possible differences.
Authors 5
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Angga M. Fuady corresponding Aachen Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands Department of Biomedical Data Sciences
Leiden University Medical Center · University Medical Center Utrecht
Affiliation as printed
Department of Biomedical Data Sciences Leiden University Medical Center Leiden the Netherlands
Department of Biostatistics and Research Support Div. Julius Centrum University Medical Center Utrecht Utrecht the Netherlands
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
Department of Biostatistics and Research Support, Div. Julius Centrum, University Medical Center Utrecht, Utrecht, the Netherlands
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Willeke van Roon‐Mom Aachen Department Human Genetics Leiden University Medical Center Leiden the Netherlands Department Human Genetics
Leiden University Medical Center
Affiliation as printed
Department Human Genetics Leiden University Medical Center Leiden the Netherlands
Department Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
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Szymon M. Kiełbasa Aachen Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands Department of Biomedical Data Sciences
Leiden University Medical Center
Affiliation as printed
Department of Biomedical Data Sciences Leiden University Medical Center Leiden the Netherlands
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
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University Medical Center Utrecht
Affiliation as printed
Department of Biostatistics and Research Support Div. Julius Centrum University Medical Center Utrecht Utrecht the Netherlands
Department of Biostatistics and Research Support, Div. Julius Centrum, University Medical Center Utrecht, Utrecht, the Netherlands
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University of Leeds · University Medical Center Utrecht
Affiliation as printed
Department of Biostatistics and Research Support Div. Julius Centrum University Medical Center Utrecht Utrecht the Netherlands
Department of Statistics and Alan Turing Institute University of Leeds Leeds United Kingdom
Department of Biostatistics and Research Support, Div. Julius Centrum, University Medical Center Utrecht, Utrecht, the Netherlands
Department of Statistics and Alan Turing Institute, University of Leeds, Leeds, United Kingdom
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