| 1. |
- Repsilber, Dirk, 1971-, et al.
(författare)
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Data rotation improves genomotyping efficiency
- 2005
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Ingår i: Biometrical Journal. - Berlin, Germany : Wiley. - 0323-3847 .- 1521-4036. ; 47:4, s. 585-598
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Tidskriftsartikel (refereegranskat)abstract
- Unsequenced bacterial strains can be characterized by comparing their genomic DNA to a sequenced reference genome of the same species. This comparative genomic approach, also called genomotyping, is leading to an increased understanding of bacterial evolution and pathogenesis. It is efficiently accomplished by comparative genomic hybridization on custom-designed cDNA microarrays. The microarray experiment results in fluorescence intensities for reference and sample genome for each gene. The logratio of these intensities is usually compared to a cut-off, classifying each gene of the sample genome as a candidate for an absent or present gene with respect to the reference genome. Reducing the usually high rate of false positives in the list of candidates for absent genes is decisive for both time and costs of the experiment. We propose a novel method to improve efficiency of genomotyping experiments in this sense, by rotating the normalized intensity data before setting up the list of candidate genes. We analyze simulated genomotyping data and also re-analyze an experimental data set for comparison and illustration. We approximately halve the proportion of false positives in the list of candidate absent genes for the example comparative genomic hybridization experiment as well as for the simulation experiments.
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| 2. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 3. |
- Jacobsen, Marc, et al.
(författare)
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Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis
- 2007
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Ingår i: Journal of Molecular Medicine. - New York, USA : Springer. - 0946-2716 .- 1432-1440. ; 85:6, s. 613-21
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Tidskriftsartikel (refereegranskat)abstract
- Infection with Mycobacterium tuberculosis is controlled by an efficacious immune response in about 90% of infected individuals who do not develop disease. Although essential mediators of protection, e.g., interferon-gamma, have been identified, these factors are insufficient to predict the outcome of M. tuberculosis infection. As a first step to determine additional biomarkers, we compared gene expression profiles of peripheral blood mononuclear cells from tuberculosis patients and M. tuberculosis-infected healthy donors by microarray analysis. Differentially expressed candidate genes were predominantly derived from monocytes and comprised molecules involved in the antimicrobial defense, inflammation, chemotaxis, and intracellular trafficking. We verified differential expression for alpha-defensin 1, alpha-defensin 4, lactoferrin, Fcgamma receptor 1A (cluster of differentiation 64 [CD64]), bactericidal permeability-increasing protein, and formyl peptide receptor 1 by quantitative polymerase chain reaction analysis. Moreover, we identified increased protein expression of CD64 on monocytes from tuberculosis patients. Candidate biomarkers were then assessed for optimal study group discrimination. Using a linear discriminant analysis, a minimal group of genes comprising lactoferrin, CD64, and the Ras-associated GTPase 33A was sufficient for classification of (1) tuberculosis patients, (2) M. tuberculosis-infected healthy donors, and (3) noninfected healthy donors.
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| 4. |
- Jacobsen, Marc, et al.
(författare)
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Deconfounding microarray analysis : independent measurements of cell type proportions used in a regression model to resolve tissue heterogeneity bias
- 2006
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Ingår i: Methods of Information in Medicine. - Stuttgart, Germany : Schattauer Gmbh. - 0026-1270 .- 2511-705X. ; 45:5, s. 557-63
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Microarray analysis requires standardized specimens and evaluation procedures to achieve acceptable results. A major limitation of this method is caused by heterogeneity in the cellular composition of tissue specimens, which frequently confounds data analysis. We introduce a linear model to deconfound gene expression data from tissue heterogeneity for genes exclusively expressed by a single cell type.Methods: Gene expression data are deconfounded from tissue heterogeneity effects by analyzing them using an appropriate linear regression model. In our illustrating data set tissue heterogeneity is being measured using flow cytometry. Gene expression data are determined in parallel by real time quantitative polymerase chain reaction (qPCR) and microarray analyses. Verification of deconfounding is enabled using protein quantification for the respective marker genes.Results: For our illustrating dataset, quantification of cell type proportions for peripheral blood mononuclear cells (PBMC) from tuberculosis patients and controls revealed differences in B cell and monocyte proportions between both study groups, and thus heterogeneity for the tissue under investigation. Gene expression analyses reflected these differences in celltype distribution. Fitting an appropriate linear model allowed us to deconfound measured transcriptome levels from tissue heterogeneity effects. In the case of monocytes, additional differential expression on the single cell level could be proposed. Protein quantification verified these deconfounded results.Conclusions: Deconfounding of transcriptome analyses for cellular heterogeneity greatly improves interpretability, and hence the validity of transcriptome profiling results.
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| 5. |
- Jacobsen, Marc, et al.
(författare)
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Ras-associated small GTPase 33A, a novel T cell factor, is down-regulated in patients with tuberculosis
- 2005
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Ingår i: Journal of Infectious Diseases. - Chicago, USA : University of Chicago Press. - 0022-1899 .- 1537-6613. ; 192:7, s. 1211-8
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Tidskriftsartikel (refereegranskat)abstract
- Ras-associated small GTPases (Rabs) are specific regulators of intracellular vesicle trafficking. Interference with host cell vesicular transport is a hallmark of many intracellular pathogens, including the notable example Mycobacterium tuberculosis. We performed, by quantitative polymerase chain reaction, gene-expression analyses for selected Rab molecules in peripheral-blood mononuclear cells from patients with tuberculosis (TB) and healthy control subjects, to identify candidate genes that are critically involved in the host immune response. Comparison revealed significant differences in the expression of genes for Rab13, Rab24, and Rab33A. Rab33A gene expression was down-regulated in patients with TB and was predominantly expressed in CD8+ T cells. We excluded possible influences of differences in T cell percentages between the 2 study groups, demonstrating that Rab33A gene expression changes on the single-cell level. In vitro, Rab33A RNA expression was induced in T cells on activation and by dendritic cells infected with M. tuberculosis. Our findings identify Rab33A as a T cell regulatory molecule in TB and suggest its involvement in disease processes.
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| 6. |
- Repsilber, Dirk, 1971-, et al.
(författare)
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Sample selection for microarray gene expression studies
- 2005
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Ingår i: Methods of Information in Medicine. - Stuttgart, Germany : Schattauer Gmbh. - 0026-1270 .- 2511-705X. ; 44:3, s. 461-7
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: The choice of biomedical samples for microarray gene expression studies is decisive for both validity and interpretability of results. We present a consistent, comprehensive framework to deal with the typical selection problems in microarray studies.Methods: Microarray studies are designed either as case-control studies or as comparisons of parallel groups from cohort studies, since high levels of random variation in the experimental approach thwart absolute measurements of gene expression levels. Validity and results of gene expression studies heavily rely on the appropriate choice of these study groups. Therefore, the so-called principles of comparability, which are well known from both clinical and epidemiological studies, need to be applied to microarray experiments.Results: The principles of comparability are the study-base principle, the principle of deconfounding and the principle of comparable accuracy in measurements. We explain each of these principles, show how they apply to microarray experiments, and illustrate them with examples. The examples are chosen as to represent typical stumbling blocks of microarray experimental design, and to exemplify the benefits of implementing the principles of comparability in the setting of microarray experiments.Conclusions: Microarray studies are closely related to classical study designs and therefore have to obey the same principles of comparability as these. Their validity should not be compromised by selection, confounding or information bias. The so-called study-base principle, calling for comparability and thorough definition of the compared cell populations, is the key principle for the choice of biomedical samples and controls in microarray studies.
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| 7. |
- Repsilber, Dirk, 1971-, et al.
(författare)
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Tutorial on microarray gene expression experiments : An introduction
- 2005
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Ingår i: Methods of Information in Medicine. - Stuttgart, Germany : Schattauer Gmbh. - 0026-1270 .- 2511-705X. ; 44:3, s. 392-9
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: With the collection of articles presented in this special issue, we aim at educating interested statisticians and biometricians on the one hand as well as biologists and medical researchers on the other with respect to basic necessities in planning, conducting and analyzing microarray gene expression experiments. The reader should get comprehensive directions to understand both the overall structure of this approach as well as the decisive details, which enable--or thwart--a meaningful data analysis.Methods: For a one-day workshop with tutorial character we brought together experts in design, conduct and analysis of microarray gene expression experiments who prepared a series of comprehensive lessons. These contributions were then reworked into a series of introductory articles and bundled in form and content as a Special Topic.Results: It was possible to present a tutorial overview of the field. The interested reader was able to learn the basic necessities and was referred to further references for details on the possible alternatives. A recipe style all-embracing plan, covering all eventualities and possibilities was not only beyond the scope of an introductory tutorial-like presentation, but was also not yet agreed upon by the scientific society.Conclusions: It proved feasible to find a framework for integrating the interdisciplinary approaches to the challenging field of gene expression analysis with microarrays, hopefully contributing to a rapid and comprehensive introduction for novices.
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| 8. |
- Repsilber, Dirk, 1971-, et al.
(författare)
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Two-color microarray experiments. Technology and sources of variance
- 2005
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Ingår i: Methods of Information in Medicine. - Stuttgart, Germany : Schattauer Gmbh. - 0026-1270 .- 2511-705X. ; 44:3, s. 400-4
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Microarray gene expression experiments have a complex technical background. Knowledge about certain technical details is inevitable to judge alternatives for both experimental design and analysis. Here, we introduce the necessary details for the so-called two-color microarray experiments and review major sources of technical variance.Methods: We follow the sequence of experimental steps during a typical two-color microarray gene expression experiment, stressing decisive points in the choice of technique, experimental handling and biophysical basics. We point out where technical variation is to be expected.Results: Tissue storage, RNA extraction techniques, as well as the microarray hybridization represent major components of technical variance to be considered. Depending on the possibilities for access to the biomedical material under investigation, choice of amplification and labeling techniques can also be decisive to avoid additional technical variance. The two-color microarray experimental approach seeks to avoid a group of probe-level technical biases making use of the advantages of an incomplete block-design.Conclusions: It is worth to know the major sources of technical variance during the typical experimental sequence, both for choice of experimental design and techniques of molecular biology, as well as for the understanding of quality control and normalization approaches. Here, early investments pay at the level of reduced technical variance, allowing for enhanced detection levels for the effects under investigation.
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| 9. |
- Snipen, Lars, et al.
(författare)
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Detection of divergent genes in microbial aCGH experiments
- 2006
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Ingår i: BMC Bioinformatics. - London, UK : BioMed Central. - 1471-2105. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Background: Array-based comparative genome hybridization (aCGH) is a tool for rapid comparison of genomes from different bacterial strains. The purpose of such analysis is to detect highly divergent or absent genes in a sample strain compared to an index strain. Development of methods for analyzing aCGH data has primarily focused on copy number abberations in cancer research. In microbial aCGH analyses, genes are typically ranked by log-ratios, and classification into divergent or present is done by choosing a cutoff log-ratio, either manually or by statistics calculated from the log-ratio distribution. As experimental settings vary considerably, it is not possible to develop a classical discriminant or statistical learning approach.Methods: We introduce a more efficient method for analyzing microbial aCGH data using a finite mixture model and a data rotation scheme. Using the average posterior probabilities from the model fitted to log-ratios before and after rotation, we get a score for each gene, and demonstrate its advantages for ranking and detecting divergent genes with enlarged specificity and sensitivity.Results: The procedure is tested and compared to other approaches on simulated data sets, as well as on four experimental validation data sets for aCGH analysis on fully sequenced strains of Staphylococcus aureus and Streptococcus pneumoniae.Conclusion: When tested on simulated data as well as on four different experimental validation data sets from experiments with only fully sequenced strains, our procedure out-competes the standard procedures of using a simple log-ratio cutoff for classification into present and divergent genes.
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