Training as infrastructure for biological data science in wartime Ukraine.
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Biomedical subjects
Publications and source records attributed to Wolfgang Huber.
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Genetic variants (both coding and noncoding) can impact gene function and expression, driving disease mechanisms such as cancer progression. The systematic study of endogenous genetic variants is hindered by inefficient precision editing tools, combined with technical limitations in confidently linking genotypes to gene expression at single-cell resolution. We developed single-cell DNA-RNA sequencing (SDR-seq) to simultaneously profile up to 480 genomic DNA loci and genes in thousands of single cells, enabling accurate determination of coding and noncoding variant zygosity alongside associated gene expression changes. Using SDR-seq, we associate coding and noncoding variants with distinct gene expression in human induced pluripotent stem cells. Furthermore, we demonstrate that in primary B cell lymphoma samples, cells with a higher mutational burden exhibit elevated B cell receptor signaling and tumorigenic gene expression. SDR-seq provides a powerful platform to dissect regulatory mechanisms encoded by genetic variants, advancing our understanding of gene expression regulation and its implications for disease.
Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems.
MOTIVATION: High-density DNA tiling microarrays are a powerful tool for the characterization of complete transcriptomes. The two major analytical challenges are the segmentation of the hybridization signal along genomic coordinates to accurately determine transcript boundaries and the adjustment of the sequence-dependent response of the oligonucleotide probes to achieve quantitative comparability of the signal between different probes. RESULTS: We describe a dynamic programming algorithm for finding a globally optimal fit of a piecewise constant expression profile along genomic coordinates. We developed a probe-specific background correction and scaling method that employs empirical probe response parameters determined from reference hybridizations with no need for paired mismatch probes. This combined analysis approach allows the accurate determination of dynamical changes in transcription architectures from hybridization data and will help to study the biological significance of complex transcriptional phenomena in eukaryotic genomes. AVAILABILITY: R package tilingArray at http://www.bioconductor.org.
There is abundant transcription from eukaryotic genomes unaccounted for by protein coding genes. A high-resolution genome-wide survey of transcription in a well annotated genome will help relate transcriptional complexity to function. By quantifying RNA expression on both strands of the complete genome of Saccharomyces cerevisiae using a high-density oligonucleotide tiling array, this study identifies the boundary, structure, and level of coding and noncoding transcripts. A total of 85% of the genome is expressed in rich media. Apart from expected transcripts, we found operon-like transcripts, transcripts from neighboring genes not separated by intergenic regions, and genes with complex transcriptional architecture where different parts of the same gene are expressed at different levels. We mapped the positions of 3' and 5' UTRs of coding genes and identified hundreds of RNA transcripts distinct from annotated genes. These nonannotated transcripts, on average, have lower sequence conservation and lower rates of deletion phenotype than protein coding genes. Many other transcripts overlap known genes in antisense orientation, and for these pairs global correlations were discovered: UTR lengths correlated with gene function, localization, and requirements for regulation; antisense transcripts overlapped 3' UTRs more than 5' UTRs; UTRs with overlapping antisense tended to be longer; and the presence of antisense associated with gene function. These findings may suggest a regulatory role of antisense transcription in S. cerevisiae. Moreover, the data show that even this well studied genome has transcriptional complexity far beyond current annotation.
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LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.
PURPOSE: To prospectively compare the protective effect of acetylcysteine, theophylline, and both agents combined in patients who are admitted to the intensive care unit with at least one risk factor for contrast material-induced nephropathy and who receive at least 100 mL of iodinated contrast medium. MATERIALS AND METHODS: Institutional ethics review board approval and informed consent were obtained. A total of 91 patients (mean age, 58.5 years+/-14.8 [standard deviation]; 31 women, 60 men; 150 examinations) were admitted to the intensive care unit with at least one risk factor for contrast-induced nephropathy and received either (a) 200 mg theophylline 30 minutes before contrast medium administration (group T), (b) 600 mg acetylcysteine twice daily on the day of and (if possible) the day before the examination (group A), or (c) both agents combined (group AT). The primary endpoint for this study was the incidence of contrast-induced nephropathy (chi2 test). RESULTS: Groups T, A, and AT were comparable with regard to baseline creatinine levels and the amount of contrast medium administered. The incidence of contrast-induced nephropathy in groups T, A, and AT was 2%, 12%, and 4%, respectively, and was significantly lower in group T than in group A (P=.047). There was no significant difference in the incidence of contrast-induced nephropathy between groups A and AT (P=.148) or between groups T and AT (P=.53). For group A, serum creatinine did not change after 12, 24, or 48 hours compared with baseline. Creatinine levels in group T decreased 12 hours (1.19 mg/dL+/-0.58; P=.008) and 48 hours (1.16 mg/dL+/-0.55; P=.034) after contrast material injection compared with baseline (1.25 mg/dL+/-0.61). In group AT, creatinine significantly decreased 24 hours (1.21 mg/dL+/-0.74; P=.003) and 48 hours (1.17 mg/dL+/-0.69; P<.001) after contrast material injection compared with baseline (1.28 mg/dL+/-0.74). Group A had significantly higher maximal increases in creatinine than groups T and AT (P=.014). CONCLUSION: For prophylaxis of contrast-induced nephropathy in patients who are admitted to the intensive care unit and who receive 100 mL or more of contrast medium, theophylline is superior to acetylcysteine.
RNA interference (RNAi) screening is a powerful technology for functional characterization of biological pathways. Interpretation of RNAi screens requires computational and statistical analysis techniques. We describe a method that integrates all steps to generate a scored phenotype list from raw data. It is implemented in an open-source Bioconductor/R package, cellHTS (http://www.dkfz.de/signaling/cellHTS). The method is useful for the analysis and documentation of individual RNAi screens. Moreover, it is a prerequisite for the integration of multiple experiments.
Cancer transcription microarray studies commonly deliver long lists of "candidate" genes that are putatively associated with the respective disease. For many of these genes, no functional information, even less their relevance in pathologic conditions, is established as they were identified in large-scale genomics approaches. Strategies and tools are thus needed to distinguish genes and proteins with mere tumor association from those causally related to cancer. Here, we describe a functional profiling approach, where we analyzed 103 previously uncharacterized genes in cancer relevant assays that probed their effects on DNA replication (cell proliferation). The genes had previously been identified as differentially expressed in genome-wide microarray studies of tumors. Using an automated high-throughput assay with single-cell resolution, we discovered seven activators and nine repressors of DNA replication. These were further characterized for effects on extracellular signal-regulated kinase 1/2 (ERK1/2) signaling (G1-S transition) and anchorage-independent growth (tumorigenicity). One activator and one inhibitor protein of ERK1/2 activation and three repressors of anchorage-independent growth were identified. Data from tumor and functional profiling make these proteins novel prime candidates for further in-depth study of their roles in cancer development and progression. We have established a novel functional profiling strategy that links genomics to cell biology and showed its potential for discerning cancer relevant modulators of the cell cycle in the candidate lists from microarray studies.
biomaRt is a new Bioconductor package that integrates BioMart data resources with data analysis software in Bioconductor. It can annotate a wide range of gene or gene product identifiers (e.g. Entrez-Gene and Affymetrix probe identifiers) with information such as gene symbol, chromosomal coordinates, Gene Ontology and OMIM annotation. Furthermore biomaRt enables retrieval of genomic sequences and single nucleotide polymorphism information, which can be used in data analysis. Fast and up-to-date data retrieval is possible as the package executes direct SQL queries to the BioMart databases (e.g. Ensembl). The biomaRt package provides a tight integration of large, public or locally installed BioMart databases with data analysis in Bioconductor creating a powerful environment for biological data mining.
Current diagnosis of renal cancer consists of histopathologic examination of tissue sections and classification into tumor stages and grades of malignancy. Until recently, molecular differences between tumor types were largely unknown. To examine such differences, we did gene expression measurements of 112 renal cell carcinoma and normal kidney samples on renal cell carcinoma-specific cDNA microarrays containing 4,207 genes and expressed sequence tags. The gene expression patterns showed deregulation of complete biological pathways in the tumors. Many of the molecular changes corresponded well to the histopathologic tumor types, and a set of 80 genes was sufficient to classify tumors with a very low error rate. Distinct gene expression signatures were associated with chromosomal abnormalities of tumor cells, metastasis formation, and patient survival. The data highlight the benefit of microarrays to detect novel tumor classes and to identify genes that are associated with patient variables and tumor properties.
To process large numbers of samples in parallel is one potential of protein microarrays for research and diagnostics. However, the application of protein arrays is currently hampered by the lack of comprehensive technological knowledge about the suitability of 2-D and 3-D slide surface coatings. We have performed a systematic study to analyze how both surface types perform in combination with different fluorescent dyes to generate significant and reproducible data. In total, we analyzed more than 100 slides containing 1152 spots each. Slides were probed against different monoclonal antibodies (mAbs) and recombinant fusion proteins. We found two surface coatings to be most suitable for protein and antibody (Ab) immobilization. These were further subjected to quantitative analyses by evaluating intraslide and slide-to-slide reproducibilities, and the linear range of target detection. In summary, we demonstrate that only suitable combinations of surface and fluorescent dyes allow the generation of highly reproducible data.
A 29-year-old woman presented to the emergency department with exhaustion, fatigue, and abdominal pain. She reported having received a diagnosis of bulimia nervosa 10 years before. On examination, she had a marked pallor and was severely malnourished. Laboratory analysis revealed a dramatically low hemoglobin level of 1.7 g/dL (ref: 11.5-15.8 g/dL). Serum iron was quantified as 1.4 micromol/L (ref: 7-26 micromol/L), ferritin as 5 ng/mL (ref: 10-120 ng/mL), and the level of serum transferrin as 212 mg/dL (ref: 200-360 mg/dL). A duodenal biopsy revealed villous atrophy in the mucosal layer indicative for celiac disease. This diagnosis was confirmed by serum levels of endomysial antibodies, tissue transglutaminase antibody, and antigliadin antibodies. The newly diagnosed gluten-sensitive enteropathy is likely to be in part responsible for the severe symptoms reported. The extent of hemoglobin decline in combination with an astonishing lack of critical symptoms seen in this patient is a rarity. We conclude that anorectic patients with severe anemia and malnutrition should be evaluated for the presence of additional somatic conditions.
We demonstrate a concept and implementation of a compendium for the classification of high-dimensional data from microarray gene expression profiles. A compendium is an interactive document that bundles primary data, statistical processing methods, figures, and derived data together with the textual documentation and conclusions. Interactivity allows the reader to modify and extend these components. We address the following questions: how much does the discriminatory power of a classifier depend on the choice of the algorithm that was used to identify it; what alternative classifiers could be used just as well; how robust is the result. The answers to these questions are essential prerequisites for validation and biological interpretation of the classifiers. We show how to use this approach by looking at these questions for a specific breast cancer microarray data set that first has been studied by Huang et al. (2003).
UNLABELLED: arrayMagic is a software package for quality control and preprocessing of two-colour cDNA microarray data. The automated analysis pipeline comprises data import, normalization, replica merging, quality diagnostics and data export. The script-based processing combines reproducibility and flexibility at high-throughput and provides quality-assured and preprocessed microarray data to high-level follow-up analysis. AVAILABILITY: The R package arrayMagic is available with BSD license at http://www.bioconductor.org CONTACT: a.buness@dkfz.de SUPPLEMENTARY INFORMATION: The package contains documentation in the form of manual pages and a vignette with a guided tour of a typical workflow.
The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.
INTRODUCTION: The evaluation of health-related quality of life is an established criterion for the evaluation of therapeutic measurement. Especially in the English language, a great number of different questionnaires have been developed. The original, English-language 12-item Oxford shoulder score (OSS) is a recently developed and validated patient-completed outcome measure specifically designed for the evaluation of patients suffering from shoulder pathology other than instability. Because of the lack of a comparable instrument in German, this questionnaire was translated into German and subsequently tested for validity and reliability in a cross-sectional study. MATERIAL AND METHODS: Translation of the OSS was done according to the guidelines in the literature. One hundred two patients completed the German version of the OSS and the SF-36. Additionally, the Constant shoulder score and the UCLA shoulder score were included into the validation process. The psychometric properties feasibility and patient-burden parameters were also tested. RESULTS: The patients completed all questionnaires. The mean time required for completing the OSS was 3 min, 25 s; the mean time required for evaluation of the questionnaire was 35 s. The internal consistency tested by the Cronbach's alpha (0.94) was high. The reproducibility tested by two different methods showed no significant difference. The construct validity showed a significant correlation between the OSS and the other scores. CONCLUSION: The instrument proved to be valid by demonstrating the same correlations predicted by standard clinical assessments and a generic patient-based instrument. Application and evaluation in clinical trial proved feasible and minimally time consuming. Therefore, the German translation of the Oxford shoulder score is a valid and reliable tool, applicable to outcome studies on shoulder patients.