777 research outputs found
Set-Based Test Procedures for the Functional Analysis of Protein Lists from Differential Analysis
No full textA simulation framework for correlated count data of features subsets in high-throughput sequencing or proteomics experiments
No full textAs part of the data processing of high-throughput-sequencing experiments count data are produced representing the amount of reads that map to specific genomic regions. Count data also arise in mass spectrometric experiments for the detection of protein-protein interactions. For evaluating new computational methods for the analysis of sequencing count data or spectral count data from proteomics experiments artificial count data is thus required. Although, some methods for the generation of artificial sequencing count data have been proposed, all of them simulate single sequencing runs, omitting thus the correlation structure between the individual genomic features, or they are limited to specific structures. We propose to draw correlated data from the multivariate normal distribution and round these continuous data in order to obtain discrete counts. In our approach, the required distribution parameters can either be constructed in different ways or estimated from real count data. Because rounding affects the correlation structure we evaluate the use of shrinkage estimators that have already been used in the context of artificial expression data from DNA microarrays. Our approach turned out to be useful for the simulation of counts for defined subsets of features such as individual pathways or GO categories
Robuste Analyse von hochdimensionalen omics-Daten mit Hilfe von Computersimulation und grafischer Visualisierung
No full textIn recent years, scientific research has faced significant challenges, including the rise of "fake news" on social media, which has complicated the public's perception of scientific truth. This is juxtaposed with the scientific principle of falsification, where hypotheses are not proven but rather refuted. Additionally, the reproducibility crisis—where many scientific findings cannot be consistently replicated—has become a pressing issue, highlighted in journals like *The American Statistician*. The discourse around p-values, with some suggesting their abandonment, underscores the call for more robust statistical analyses to ensure trustworthy scientific conclusions. This work explores methods to validate and enhance the robustness of statistical techniques for their effective application in real-world data scenarios. In clinical research, the objective of translating findings from the laboratory to patient care is crucial. This is structured by the 4T model: starting from basic research (T1), moving to evidence-based guidelines (T2), then transforming into clinical practices (T3), and finally improving community health outcomes (T4). Throughout these stages, biometry and statistical bioinformatics play a vital by developing robust methods that can validate clinical research findings. For example, the median offers a robust measure of central tendency less affected by outliers compared to the mean, thus providing more reliable results. The era of "big data" has led to unprecedented data volumes, posing new challenges in data management and analysis, and giving rise to the field of data science. In biometry, big data challenges were first encountered with genetic microarray technology, presenting the "high-dimensional data problem" where the number of parameters exceeds the sample size. This is illustrated in genome-wide association studies (GWAS), where genetic data consisting of hundreds of thousands of variants are analyzed to predict and classify diseases such as rheumatoid arthritis, demonstrating the necessity for innovative data processing and analytical methods to manage such complex datasets effectively
Zeig mir Health Data Science! : Ideen und Material für guten Biometrie-Unterricht mit datenwissenschaftlichem Fokus
No full textIn diesem Buch sind Lehrbeispiele gesammelt, die Dozierenden wertvolle Anregungen für ihre eigene Lehre liefern: Es werden Ideen für einzelne Übungen, Unterrichtseinheiten, Prüfungen oder ganze Kurse vorgestellt. Die benötigten Materialien sind für die Nutzer online frei verfügbar, um die Anwendung zu vereinfachen.
Alle Beiträge dieses Buches wurden 2020 für den Preis für das beste Health-Data-Science-Lehrmaterial eingereicht, der von der Arbeitsgruppe Lehre und Didaktik der Biometrie der Deutschen Region der Internationalen Biometrischen Gesellschaft und der GMDS ausgeschrieben wurde. So entstand ein breiter Querschnitt an Beiträgen für lebendige Lehre in Biometrie, Epidemiologie, Public Health und ähnlichen Gebieten.
Das Buch knüpft damit an die beiden Bände Zeig mir Biostatistik! und Zeig mir mehr Biostatistik! an, denen ähnliche Ausschreibungen vorausgingen.
Die Herausgeber unterrichten Biometrie als Haupt- oder Nebenfach an verschiedenen Universitäten bzw. Hochschulen. Es verbindet sie das gemeinsame Ziel, den Austausch von Ideen und ausgereiftem Unterrichtsmaterial im Bereich Health Data Science zu fördern
A Simple Test Identifies Selection on Complex Traits
No full textAbstract
Important traits are often controlled by a large number of genes that each impact a small proportion of total variation; however, the majority of tools in population genomics are designed to identify single genes...</jats:p
Risk prediction with machine learning and regression methods
No full textThis is a discussion of issues in risk prediction based on the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gerard Biau, Michael Kohler, Inke R. Konig, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. Konig, and Andreas Ziegler
Gene loss and lineage specific restriction-modification systems associated with niche differentiation in the Campylobacter jejuni Sequence Type 403 clonal complex
No full textCampylobacter jejuni is a highly diverse species of bacteria commonly associated with infectious intestinal disease of humans and zoonotic carriage in poultry, cattle, pigs, and other animals. The species contains a large number of distinct clonal complexes that vary from host generalist lineages commonly found in poultry, livestock, and human disease cases to host-adapted specialized lineages primarily associated with livestock or poultry. Here, we present novel data on the ST403 clonal complex of C. jejuni, a lineage that has not been reported in avian hosts. Our data show that the lineage exhibits a distinctive pattern of intralineage recombination that is accompanied by the presence of lineage-specific restriction-modification systems. Furthermore, we show that the ST403 complex has undergone gene decay at a number of loci. Our data provide a putative link between the lack of association with avian hosts of C. jejuni ST403 and both gene gain and gene loss through nonsense mutations in coding sequences of genes, resulting in pseudogene formation
Crohn's disease patient serum changes protein expression in a human mesenchymal stem cell model in a linear relationship to patients' disease stage and to bone mineral density.
No full textBackground: Crohn's disease (CD) is associated with a higher prevalence of osteoporosis, a complication that is recognized as a significant cause of morbidity. Its pathogenesis is controversial, but the activity of CD is one contributing factor. Methods: We stimulated SCP-1 cells (mesenchymal stem cell line) under osteogenic conditions with serum from adult patients with CD in the symptomatic phase (SP) and in remission (R) and with control sera. Concentrations of IL-6, IL-1 beta, and TNF alpha in the sera were measured. Patients were classified as normal or osteopenic/osteoporotic based on bone mineral density (BMD) T-score measurements. After 14 days in culture, protein expression and gene ontology (GO) annotation analysis was performed. Results: Cytokine concentrations (IL-6, IL-1 beta, TNF alpha) varied within sera groups. None of the cytokines were significantly increased in the symptomatic phase compared to remission. Protein analysis revealed 17 proteins regulated by the SP versus R phase sera of disease. A linear relationship between CDAI (Crohn's disease activity index) and normalized protein expression of APOA1 and 2, TTR, CDKAL1 and TUBB6 could be determined. Eleven proteins were found to be differentially regulated comparing osteoporosis-positive and osteoporosis-negative sera. Gene annotation and further analysis identified these genes as part of heme and erythrocyte metabolism, as well as involved in hypoxia and in endocytosis. A significant linear relationship between bone mineral density and normalized protein expression could be determined for proteins FABP3 and TTR. Conclusion: Our explorative results confirm our hypothesis that factors in serum from patients with CD change the protein expression pattern of human immortalized osteoblast like cells. We suggest, that these short time changes indeed influence factors of bone metabolism
Supplemental Material, DS1_VET_10.1177_0300985818755253 - Canine Bocavirus Type 2 Infection Associated With Intestinal Lesions
No full textSupplemental Material, DS1_VET_10.1177_0300985818755253 for Canine Bocavirus Type 2 Infection Associated With Intestinal Lesions by Chutchai Piewbang, Wendy K. Jo, Christina Puff, Martin Ludlow, Erhard van der Vries, Wijit Banlunara, Anudep Rungsipipat, Jochen Kruppa, Klaus Jung, Somporn Techangamsuwan, Wolfgang Baumgärtner, and Albert D. M. E. Osterhaus in Veterinary Pathology</p
Influence of Duration till Beginning of an antibiotic Therapy on Outcome in Patients,who were treated with neuroprotective therapeutic Hypothermia after primary survival of Cardiovascular Arrest outside hospital
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