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- Finn, Robert D, et al.
(författare)
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Pfam : clans, web tools and services.
- 2006
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Ingår i: Nucleic Acids Res. - : Oxford University Press (OUP). - 1362-4962 .- 0305-1048. ; 34:Database issue, s. D247-51
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Tidskriftsartikel (refereegranskat)
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| 2. |
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| 3. |
- Pettersson-Kymmer, Ulrika, et al.
(författare)
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HLA and KIR Associations of Cervical Neoplasia
- 2018
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Ingår i: Journal of Infectious Diseases. - : Oxford University Press. - 0022-1899 .- 1537-6613. ; 218:12, s. 2006-2015
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Tidskriftsartikel (refereegranskat)abstract
- Background: Cervical cancer is the fourth most common cancer in women, and we recently reported human leukocyte antigen (HLA) alleles showing strong associations with cervical neoplasia risk and protection. HLA ligands are recognised by killer immunoglobulin-like receptors (KIRs) expressed on a range of immune cell subsets, governing their proinflammatory activity. We hypothesized that the inheritance of particular HLA-KIR combinations would increase cervical neoplasia risk.Methods: Here, we used HLA and KIR dosages imputed from SNP genotype data from 2,143 cervical neoplasia cases and 13,858 healthy controls of European decent.Results: Four novel HLA alleles were identified in association with cervical neoplasia: HLA-DRB3*9901 (OR=1.24, P=2.49×10-9), HLA-DRB5*0101 (OR=1.29, P=2.26×10-8), HLA-DRB5*9901 (OR=0.77, P=1.90×10-9) and HLA-DRB3*0301 (OR=0.63, P=4.06×10-5), due to their linkage disequilibrium with known cervical neoplasia-associated HLA-DRB1 alleles. We also found homozygosity of HLA-C1 group alleles is a protective factor for HPV16-related cervical neoplasia (C1/C1, OR=0.79, P=0.005). This protective association was restricted to carriers of either KIR2DL2 (OR=0.67, P=0.00045) or KIR2DS2 (OR=0.69, P=0.0006).Conclusions: Our findings suggest that HLA-C1 group alleles play a role in protecting against HPV16-related cervical neoplasia, mainly through a KIR-mediated mechanism.
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| 4. |
- Schweinsberg, Martin, et al.
(författare)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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Ingår i: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Tidskriftsartikel (refereegranskat)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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| 5. |
- Zheng, Hou-Feng, et al.
(författare)
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Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 526:7571, s. 112-
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Tidskriftsartikel (refereegranskat)abstract
- The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF <= 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants(1-8), as well as rare, population specific, coding variants(9). Here we identify novel non-coding genetic variants with large effects on BMD (n(total) = 53,236) and fracture (n(total) = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD8 (rs11692564(T), MAF51.6%, replication effect size510.20 s.d., P-meta = 2 x 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 x 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size +10.41 s.d., P-meta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.
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