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10 results on '"Luetge, Almut"'

1. Omnibenchmark (alpha) for continuous and open benchmarking in bioinformatics

Author

Mallona, Izaskun, Luetge, Almut, Carrillo, Ben, Incicau, Daniel, Gerber, Reto, Sonrel, Anthony, Soneson, Charlotte, and Robinson, Mark D.

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

Benchmarking in bioinformatics is a process of designing, running and disseminating rigorous performance evaluations of methods (software). Benchmarking systems facilitate the benchmarking process by providing an entrypoint to store, coordinate and execute concrete benchmarks. We describe an alpha version of a new benchmarking system, Omnibenchmark, to facilitate benchmark formalization and execution in solo and community efforts. Omnibenchmark provides a benchmark definition syntax (in a configuration YAML file), a dynamic workflow generation based on Snakemake, S3-compatible storage handling, and reproducible software environments using EasyBuild, lmod, Apptainer or conda. Tutorials and installation instructions are available from https://omnibenchmark.org., Comment: 7 pages, 1 figure, 1 table

Published
2024

2. Building a continuous benchmarking ecosystem in bioinformatics

Author

Mallona, Izaskun, Luetge, Almut, Soneson, Charlotte, Carrillo, Ben, Gerber, Reto, Incicau, Daniel, Sonrel, Anthony, and Robinson, Mark D.

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

Benchmarking, which involves collecting reference datasets and demonstrating method performances, is a requirement for the development of new computational tools, but also becomes a domain of its own to achieve neutral comparisons of methods. Although a lot has been written about how to design and conduct benchmark studies, this Perspective sheds light on a wish list for a computational platform to orchestrate benchmark studies. We discuss various ideas for organizing reproducible software environments, formally defining benchmarks, orchestrating standardized workflows, and how they interface with computing infrastructure., Comment: 21 pages, 2 figures, 1 table

Published
2024

3. Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability

Author

Sonrel, Anthony, Luetge, Almut, Soneson, Charlotte, Mallona, Izaskun, Germain, Pierre-Luc, Knyazev, Sergey, Gilis, Jeroen, Gerber, Reto, Seurinck, Ruth, Paul, Dominique, Sonder, Emanuel, Crowell, Helena L., Fanaswala, Imran, Al-Ajami, Ahmad, Heidari, Elyas, Schmeing, Stephan, Milosavljevic, Stefan, Saeys, Yvan, Mangul, Serghei, and Robinson, Mark D.

Published
2023
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4. Additional file 4 of Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability

Author

Sonrel, Anthony, Luetge, Almut, Soneson, Charlotte, Mallona, Izaskun, Germain, Pierre-Luc, Knyazev, Sergey, Gilis, Jeroen, Gerber, Reto, Seurinck, Ruth, Paul, Dominique, Sonder, Emanuel, Crowell, Helena L., Fanaswala, Imran, Al-Ajami, Ahmad, Heidari, Elyas, Schmeing, Stephan, Milosavljevic, Stefan, Saeys, Yvan, Mangul, Serghei, and Robinson, Mark D.

Abstract

Additional file 4: Figure S1. Auxiliary summaries from the survey responses. Simulator used, secondary measures assessed, language of tools assessed.

Published
2023
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5. Additional file 5 of Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability

Author

Sonrel, Anthony, Luetge, Almut, Soneson, Charlotte, Mallona, Izaskun, Germain, Pierre-Luc, Knyazev, Sergey, Gilis, Jeroen, Gerber, Reto, Seurinck, Ruth, Paul, Dominique, Sonder, Emanuel, Crowell, Helena L., Fanaswala, Imran, Al-Ajami, Ahmad, Heidari, Elyas, Schmeing, Stephan, Milosavljevic, Stefan, Saeys, Yvan, Mangul, Serghei, and Robinson, Mark D.

Abstract

Additional file 5. Review history.

Published
2023
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6. Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology

Author

Bjornsdottir, Gyda, Stefánsdóttir, Lilja, Thorleifsson, Gudmar, Sulem, Patrick, Norland, Kristjan, Ferkingstad, Egil, Oddsson, Asmundur, Zink, Florian, Lund, Sigrun H., Nawaz, Muhammad S., Bragi Walters, G., Skuladottir, Astros Th., Gudjonsson, Sigurjon A., Einarsson, Gudmundur, Halldorsson, Gisli H., Bjarnadottir, Valgerdur, Sveinbjornsson, Gardar, Helgadottir, Anna, Styrkársdóttir, Unnur, Gudmundsson, Larus J., Pedersen, Ole B., Hansen, Thomas Folkmann, Werge, Thomas, Banasik, Karina, Troelsen, Anders, Skou, Soren T., Thørner, Lise Wegner, Erikstrup, Christian, Nielsen, Kaspar Rene, Mikkelsen, Susan, Andersen, Steffen, Brunak, Søren, Burgdorf, Kristoffer, Hjalgrim, Henrik, Jemec, Gregor, Jennum, Poul, Johansson, Per Ingemar, Nielsen, Kasper Rene, Nyegaard, Mette, Bruun, Mie Topholm, Pedersen, Ole Birger, Dinh, Khoa Manh, Sørensen, Erik, Ostrowski, Sisse R., Johansson, Pär Ingemar, Gudbjartsson, Daniel F., Stefansson, Hreinn, Þorsteinsdóttir, Unnur, Larsen, Margit Anita Hørup, Didriksen, Maria, Sækmose, Susanne, Zeggini, Eleftheria, Hatzikotoulas, Konstantinos, Southam, Lorraine, Gilly, Arthur, Barysenka, Andrei, van Meurs, Joyce B. J., Boer, Cindy G., Uitterlinden, André G., Jonsson, Helgi, Ingvarsson, Thorvaldur, Esko, Tõnu, Mägi, Reedik, Teder-Laving, Maris, Ikegawa, Shiro, Terao, Chikashi, Takuwa, Hiroshi, Meulenbelt, Ingrid, Coutinho de Almeida, Rodrigo, Kloppenburg, Margreet, Tuerlings, Margo, Slagboom, P. Eline, Nelissen, Rob R. G. H. H., Valdes, Ana M., Mangino, Massimo, Tsezou, Aspasia, Zengini, Eleni, Alexiadis, George, Babis, George C., Cheah, Kathryn S. E., Wu, Tian T., Samartzis, Dino, Cheung, Jason Pui Yin, Sham, Pak Chung, Kraft, Peter, Kang, Jae Hee, Hveem, Kristian, Zwart, John-Anker, Luetge, Almut, Skogholt, Anne Heidi, Johnsen, Marianne B., Thomas, Laurent F., Winsvold, Bendik, Gabrielsen, Maiken E., Lee, Ming Ta Michael, Zhang, Yanfei, Lietman, Steven A., Shivakumar, Manu, Smith, George Davey, Tobias, Jonathan H., Hartley, April, Gaunt, Tom R., Zheng, Jie, Wilkinson, J. Mark, Steinberg, Julia, Morris, Andrew P., Jonsdottir, Ingileif, Bjornsson, Aron, Olafsson, Ingvar H., Ulfarsson, Elfar, Blondal, Josep, Vikingsson, Arnor, Brunak, Soren, Ullum, Henrik, Thorsteinsdottir, Unnur, Thorgeirsson, Thorgeir E., Stefansson, Kari, Consortium, DBDS Genetic, Consortium, GO, and Internal Medicine

Subjects
Science, General Physics and Astronomy, Intervertebral Disc Degeneration, Intervertebral Disc/metabolism, Bone and Bones/metabolism, Bone and Bones, General Biochemistry, Genetics and Molecular Biology, health services administration, Humans, Sodium Sulfate Cotransporter/genetics, Intervertebral Disc, 3' Untranslated Regions, health care economics and organizations, Sodium Sulfate Cotransporter, Symporters/genetics, Multidisciplinary, Symporters, Sulfates, General Chemistry, equipment and supplies, Intervertebral Disc Degeneration/genetics, Intervertebral Disc Displacement/genetics, Sulfates/metabolism, population characteristics, human activities, Intervertebral Disc Displacement, Genome-Wide Association Study
Abstract

Back pain is a common and debilitating disorder with largely unknown underlying biology. Here we report a genome-wide association study of back pain using diagnoses assigned in clinical practice; dorsalgia (119,100 cases, 909,847 controls) and intervertebral disc disorder (IDD) (58,854 cases, 922,958 controls). We identify 41 variants at 33 loci. The most significant association (ORIDD = 0.92, P = 1.6 × 10−39; ORdorsalgia = 0.92, P = 7.2 × 10−15) is with a 3’UTR variant (rs1871452-T) in CHST3, encoding a sulfotransferase enzyme expressed in intervertebral discs. The largest effects on IDD are conferred by rare (MAF = 0.07 − 0.32%) loss-of-function (LoF) variants in SLC13A1, encoding a sodium-sulfate co-transporter (LoF burden OR = 1.44, P = 3.1 × 10−11); variants that also associate with reduced serum sulfate. Genes implicated by this study are involved in cartilage and bone biology, as well as neurological and inflammatory processes.

Published
2022

7. Using multivariable Mendelian randomization to estimate the causal effect of bone mineral density on osteoarthritis risk, independently of body mass index

Author

Hartley, April, Sanderson, Eleanor, Granell, Raquel, Paternoster, Lavinia, Zheng, Jie, Smith, George Davey, Southam, Lorraine, Hatzikotoulas, Konstantinos, Boer, Cindy G., Van Meurs, Joyce, Zeggini, Eleftheria, Gregson, Celia L., Tobias, Jon H., Stefánsdóttir, Lilja, Zhang, Yanfei, De Almeida, Rodrigo Coutinho, Wu, Tian T., Teder-Laving, Maris, Skogholt, Anne Heidi, Terao, Chikashi, Zengini, Eleni, Alexiadis, George, Barysenka, Andrei, Bjornsdottir, Gyda, Gabrielsen, Maiken E., Gilly, Arthur, Ingvarsson, Thorvaldur, Johnsen, Marianne B., Jonsson, Helgi, Kloppenburg, Margreet G., Luetge, Almut, Mägi, Reedik, Mangino, Massimo, Nelissen, Rob R.G.H.H., Shivakumar, Manu, Steinberg, Julia, Takuwa, Hiroshi, Thomas, Laurent, Tuerlings, Margo, Babis, George, Cheung, Jason Pui Yin, Samartzis, Dino, Lietman, Steve A., Slagboom, P. Eline, Stefansson, Kari, Uitterlinden, André G., Winsvold, Bendik, Zwart, John Anker, Sham, Pak Chung, Thorleifsson, Gudmar, Gaunt, Tom R., Morris, Andrew P., Valdes, Ana M., Tsezou, Aspasia, Cheah, Kathryn S.E., Ikegawa, Shiro, Hveem, Kristian, Esko, Tõnu, Wilkinson, J. Mark, Meulenbelt, Ingrid, Michael Lee, Ming Ta, Styrkársdóttir, Unnur, and Internal Medicine

Subjects
Oncology, musculoskeletal diseases, medicine.medical_specialty, UK Biobank, Epidemiology, body mass index, Osteoarthritis, Polymorphism, Single Nucleotide, Genetic correlation, Body Mass Index, Mendelian Randomization, Uk Biobank, Bone Mineral Density, Bone Density, Internal medicine, Mendelian randomization, medicine, Humans, Allele, Risk factor, Bone mineral, business.industry, General Medicine, Mendelian Randomization Analysis, Osteoarthritis, Knee, medicine.disease, Causality, Observational study, business, bone mineral density, Body mass index, Genome-Wide Association Study
Abstract

Objectives Observational analyses suggest that high bone mineral density (BMD) is a risk factor for osteoarthritis (OA); it is unclear whether this represents a causal effect or shared aetiology and whether these relationships are body mass index (BMI)-independent. We performed bidirectional Mendelian randomization (MR) to uncover the causal pathways between BMD, BMI and OA. Methods One-sample (1S)MR estimates were generated by two-stage least-squares regression. Unweighted allele scores instrumented each exposure. Two-sample (2S)MR estimates were generated using inverse-variance weighted random-effects meta-analysis. Multivariable MR (MVMR), including BMD and BMI instruments in the same model, determined the BMI-independent causal pathway from BMD to OA. Latent causal variable (LCV) analysis, using weight-adjusted femoral neck (FN)–BMD and hip/knee OA summary statistics, determined whether genetic correlation explained the causal effect of BMD on OA. Results 1SMR provided strong evidence for a causal effect of BMD estimated from heel ultrasound (eBMD) on hip and knee OA {odds ratio [OR]hip = 1.28 [95% confidence interval (CI) = 1.05, 1.57], p = 0.02, ORknee = 1.40 [95% CI = 1.20, 1.63], p = 3 × 10–5, OR per standard deviation [SD] increase}. 2SMR effect sizes were consistent in direction. Results suggested that the causal pathways between eBMD and OA were bidirectional (βhip = 1.10 [95% CI = 0.36, 1.84], p = 0.003, βknee = 4.16 [95% CI = 2.74, 5.57], p = 8 × 10–9, β = SD increase per doubling in risk). MVMR identified a BMI-independent causal pathway between eBMD and hip/knee OA. LCV suggested that genetic correlation (i.e. shared genetic aetiology) did not fully explain the causal effects of BMD on hip/knee OA. Conclusions These results provide evidence for a BMI-independent causal effect of eBMD on OA. Despite evidence of bidirectional effects, the effect of BMD on OA did not appear to be fully explained by shared genetic aetiology, suggesting a direct action of bone on joint deterioration.

Published
2022

8. Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability

Author

Sonrel, Anthony, primary, Luetge, Almut, additional, Soneson, Charlotte, additional, Mallona, Izaskun, additional, Germain, Pierre-Luc, additional, Knyazev, Sergey, additional, Gilis, Jeroen, additional, Gerber, Reto, additional, Seurinck, Ruth, additional, Paul, Dominique, additional, Sonder, Emanuel, additional, Crowell, Helena L., additional, Fanaswala, Imran, additional, Al-Ajami, Ahmad, additional, Heidari, Elyas, additional, Schmeing, Stephan, additional, Milosavljevic, Stefan, additional, Saeys, Yvan, additional, Mangul, Serghei, additional, and Robinson, Mark D., additional

Published
2022
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9. Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Author

Boer, Cindy G., Hatzikotoulas, Konstantinos, Southam, Lorraine, Stefánsdóttir, Lilja, Zhang, Yanfei, Coutinho de Almeida, Rodrigo, Wu, Tian T., Zheng, Jie, Hartley, April, Teder-Laving, Maris, Skogholt, Anne Heidi, Terao, Chikashi, Zengini, Eleni, Alexiadis, George, Barysenka, Andrei, Bjornsdottir, Gyda, Gabrielsen, Maiken E., Gilly, Arthur, Ingvarsson, Thorvaldur, Johnsen, Marianne B., Jonsson, Helgi, Kloppenburg, Margreet, Luetge, Almut, Lund, Sigrun H., Mägi, Reedik, Mangino, Massimo, Nelissen, Rob R.G.H.H., Shivakumar, Manu, Steinberg, Julia, Takuwa, Hiroshi, Thomas, Laurent F., Tuerlings, Margo, Babis, George C., Cheung, Jason Pui Yin, Kang, Jae Hee, Kraft, Peter, Lietman, Steven A., Samartzis, Dino, Slagboom, P. Eline, Stefansson, Kari, Thorsteinsdottir, Unnur, Tobias, Jonathan H., Uitterlinden, André G., Winsvold, Bendik, Zwart, John-Anker, Davey Smith, George, Sham, Pak Chung, Thorleifsson, Gudmar, Gaunt, Tom R., Morris, Andrew P., Valdes, Ana M., Tsezou, Aspasia, Cheah, Kathryn S.E., Ikegawa, Shiro, Hveem, Kristian, Esko, Tõnu, Wilkinson, J. Mark, Meulenbelt, Ingrid, Lee, Ming Ta Michael, van Meurs, Joyce B.J., Styrkársdóttir, Unnur, and Zeggini, Eleftheria

Published
2021
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