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- Liemohn, Michael W., et al.
(författare)
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Model Evaluation Guidelines for Geomagnetic Index Predictions
- 2018
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Ingår i: Space Weather. - 1542-7390. ; 16:12, s. 2079-2102
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Tidskriftsartikel (refereegranskat)abstract
- Geomagnetic indices are convenient quantities that distill the complicated physics of some region or aspect of near‐Earth space into a single parameter. Most of the best‐known indices are calculated from ground‐based magnetometer data sets, such as Dst, SYM‐H, Kp, AE, AL, and PC. Many models have been created that predict the values of these indices, often using solar wind measurements upstream from Earth as the input variables to the calculation. This document reviews the current state of models that predict geomagnetic indices and the methods used to assess their ability to reproduce the target index time series. These existing methods are synthesized into a baseline collection of metrics for benchmarking a new or updated geomagnetic index prediction model. These methods fall into two categories: (1) fit performance metrics such as root‐mean‐square error and mean absolute error that are applied to a time series comparison of model output and observations and (2) event detection performance metrics such as Heidke Skill Score and probability of detection that are derived from a contingency table that compares model and observation values exceeding (or not) a threshold value. A few examples of codes being used with this set of metrics are presented, and other aspects of metrics assessment best practices, limitations, and uncertainties are discussed, including several caveats to consider when using geomagnetic indices.
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| 2. |
- Rothwell, S, et al.
(författare)
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Focused HLA analysis in Caucasians with myositis identifies significant associations with autoantibody subgroups
- 2019
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 78:7, s. 996-1002
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Tidskriftsartikel (refereegranskat)abstract
- Idiopathic inflammatory myopathies (IIM) are a spectrum of rare autoimmune diseases characterised clinically by muscle weakness and heterogeneous systemic organ involvement. The strongest genetic risk is within the major histocompatibility complex (MHC). Since autoantibody presence defines specific clinical subgroups of IIM, we aimed to correlate serotype and genotype, to identify novel risk variants in the MHC region that co-occur with IIM autoantibodies.MethodsWe collected available autoantibody data in our cohort of 2582 Caucasian patients with IIM. High resolution human leucocyte antigen (HLA) alleles and corresponding amino acid sequences were imputed using SNP2HLA from existing genotyping data and tested for association with 12 autoantibody subgroups.ResultsWe report associations with eight autoantibodies reaching our study-wide significance level of p<2.9×10–5. Associations with the 8.1 ancestral haplotype were found with anti-Jo-1 (HLA-B*08:01, p=2.28×10–53 and HLA-DRB1*03:01, p=3.25×10–9), anti-PM/Scl (HLA-DQB1*02:01, p=1.47×10–26) and anti-cN1A autoantibodies (HLA-DRB1*03:01, p=1.40×10–11). Associations independent of this haplotype were found with anti-Mi-2 (HLA-DRB1*07:01, p=4.92×10–13) and anti-HMGCR autoantibodies (HLA-DRB1*11, p=5.09×10–6). Amino acid positions may be more strongly associated than classical HLA associations; for example with anti-Jo-1 autoantibodies and position 74 of HLA-DRB1 (p=3.47×10–64) and position 9 of HLA-B (p=7.03×10–11). We report novel genetic associations with HLA-DQB1 anti-TIF1 autoantibodies and identify haplotypes that may differ between adult-onset and juvenile-onset patients with these autoantibodies.ConclusionsThese findings provide new insights regarding the functional consequences of genetic polymorphisms within the MHC. As autoantibodies in IIM correlate with specific clinical features of disease, understanding genetic risk underlying development of autoantibody profiles has implications for future research.
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