oposSOM-Browser: an interactive tool to explore omics data landscapes in health science

Loeffler‐Wirth, Henry; Reikowski, Jasmin; Hakobyan, Siras; Wagner, Jonas; Binder, Hans

doi:10.1186/s12859-020-03806-w

Cited by 12 publications

(24 citation statements)

References 11 publications

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“…For more detailed interactive discovery of the dataset presented in this publication we offer the oposSOM-browser platform ( (accessed on 3 March 2021)) [ 61 ]. It consists of an overview window and six ‘sub-’browser functions.…”

Section: Resultsmentioning

confidence: 99%

“…The results of transcriptome analyses presented in this publication can be interactively discovered regarding further details using the oposSOM browser [ 61 ] available on the Internet under (accessed on 3 March 2021). Functionalities include browsing (i) single gene profiles across the biopsy samples and the expression landscape, (ii) gene set profiles, (iii) different types of expression and phenotype maps, (iv) sample and subtype diversity, (v) marker signatures, and (vi) KEGG-pathway activation in the different groups.…”

Section: Methodsmentioning

confidence: 99%

“… The interactive data-browser enables detailed study of different aspects of the CD-transcriptome dataset [ 61 ] ( (accessed on 3 March 2021)). ( A ) The map browser (shown as screenshot) provides feature (genes, gene sets) lists and profiles of selected spot-areas of the SOM.…”

Section: Figurementioning

confidence: 99%

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Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies

Wolf

Willscher

Loeffler‐Wirth

et al. 2021

IJMS

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Coeliac disease (CD) is a clinically heterogeneous autoimmune disease with variable presentation and progression triggered by gluten intake. Molecular or genetic factors contribute to disease heterogeneity, but the reasons for different outcomes are poorly understood. Transcriptome studies of tissue biopsies from CD patients are scarce. Here, we present a high-resolution analysis of the transcriptomes extracted from duodenal biopsies of 24 children and adolescents with active CD and 21 individuals without CD but with intestinal afflictions as controls. The transcriptomes of CD patients divide into three groups—a mixed group presenting the control cases, and CD-low and CD-high groups referring to lower and higher levels of CD severity. Persistence of symptoms was weakly associated with subgroup, but the highest marsh stages were present in subgroup CD-high, together with the highest cell cycle rates as an indicator of virtually complete villous atrophy. Considerable variation in inflammation-level between subgroups was further deciphered into immune cell types using cell type de-convolution. Self-organizing maps portrayal was applied to provide high-resolution landscapes of the CD-transcriptome. We find asymmetric patterns of miRNA and long non-coding RNA and discuss the effect of epigenetic regulation. Expression of genes involved in interferon gamma signaling represent suitable markers to distinguish CD from non-CD cases. Multiple pathways overlay in CD biopsies in different ways, giving rise to heterogeneous transcriptional patterns, which potentially provide information about etiology and the course of the disease.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies

Wolf

Willscher

Loeffler‐Wirth

et al. 2021

IJMS

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“…Further details of the analysis of the SARS-CoV-2 genome addressed in this publication can be interactively discovered using the oposSOM browser [ 27 ] available online via the IZBI web page ( and ). The browser enables selection and visualization of SNVs in the genome landscape, and assessment of similarity relations between the variants and lineages together with their individual SOM portraits (see also Appendix B , Figure A11 and Figure A12 ).…”

Section: Methodsmentioning

confidence: 99%

“…File S1: Gallery of SOM-portraits of SARS-CoV-2 genomes (File_S1.PDF); File S2: List of SNV (position in the SARS-CoV-2 genome, amino-acid substitution, spot). Data Availability Statement: Details of the SARS-CoV-2 genome SOM portrayal can be interactively discovered using the oposSOM browser [27] available online via the IZBI web page (https://www.izbi.uni-leipzig.de/opossom-browser/ and https://apps.health-atlas.de/opossombrowser/?dataset=12). The browser enables selection and visualization of SNVs in the genome landscape and assessment of similarity relations between the variants and lineages together with their individual SOM portraits (Figures A11 and A12).…”

Section: Supplementary Materialsmentioning

confidence: 99%

The Evolving Faces of the SARS-CoV-2 Genome

Schmidt

Arshad

Bernhart

et al. 2021

Viruses

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Surveillance of the evolving SARS-COV-2 genome combined with epidemiological monitoring and emerging vaccination became paramount tasks to control the pandemic which is rapidly changing in time and space. Genomic surveillance must combine generation and sharing sequence data with appropriate bioinformatics monitoring and analysis methods. We applied molecular portrayal using self-organizing maps machine learning (SOM portrayal) to characterize the diversity of the virus genomes, their mutual relatedness and development since the beginning of the pandemic. The genetic landscape obtained visualizes the relevant mutations in a lineage-specific fashion and provides developmental paths in genetic state space from early lineages towards the variants of concern alpha, beta, gamma and delta. The different genes of the virus have specific footprints in the landscape reflecting their biological impact. SOM portrayal provides a novel option for ‘bioinformatics surveillance’ of the pandemic, with strong odds regarding visualization, intuitive perception and ‘personalization’ of the mutational patterns of the virus genomes.

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The Leipzig Health Atlas—An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online

et al. 2022

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Background: Clinical trials, epidemiological studies, clinical registries and other prospective research projects, together with patient care services, are main sources of data in the medical research domain. They serve often as basis for secondary research in evidence-based medicine, prediction models for disease and its progression. This data is often neither sufficiently described nor accessible. Related models are often not accessible as functional program tool for interested users from the healthcare and biomedical domains. Objective: The interdisciplinary project Leipzig Health Atlas (LHA) has been developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies and other medical research projects. Methods: Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for non-published data. LHA provides and associates unique permanent identifiers for each data set and model. Hence, the platform can be used to share prepared, quality assured data sets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups. Results: The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.

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oposSOM-Browser: an interactive tool to explore omics data landscapes in health science

Cited by 12 publications

References 11 publications

Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies

Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies

The Evolving Faces of the SARS-CoV-2 Genome

The Leipzig Health Atlas—An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online

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