| 1. |
- Niemi, MEK, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 2. |
- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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| 8. |
- Romagnoni, A, et al.
(författare)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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| 9. |
- Astuto, L. M., et al.
(författare)
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CDH23 mutation and phenotype heterogeneity : a profile of 107 diverse families with Usher syndrome and nonsyndromic deafness
- 2002
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 71:2, s. 262-275
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Tidskriftsartikel (refereegranskat)abstract
- Usher syndrome type I is characterized by congenital hearing loss, retinitis pigmentosa (RP), and variable vestibular areflexia. Usher syndrome type ID, one of seven Usher syndrome type I genetic localizations, have been mapped to a chromosomal interval that overlaps with a nonsyndromic-deafness localization, DFNB12. Mutations in CDH23, a gene that encodes a putative cell-adhesion protein with multiple cadherin-like domains, are responsible for both Usher syndrome and DFNB12 nonsyndromic deafness. Specific CDH23 mutational defects have been identified that differentiate these two phenotypes. Only missense mutations of CDH23 have been observed in families with nonsyndromic deafness, whereas nonsense, frameshift, splice-site, and missense mutations have been identified in families with Usher syndrome. In the present study, a panel of 69 probands with Usher syndrome and 38 probands with recessive nonsyndromic deafness were screened for the presence of mutations in the entire coding region of CDH23, by heteroduplex, single-strand conformation polymorphism, and direct sequence analyses. A total of 36 different CDH23 mutations were detected in 45 families; 33 of these mutations were novel, including 18 missense, 3 nonsense, 5 splicing defects, 5 microdeletions, and 2 insertions. A total of seven mutations were common to more than one family. Numerous exonic and intronic polymorphisms also were detected. Results of ophthalmologic examinations of the patients with nonsyndromic deafness have found asymptomatic RP-like manifestations, indicating that missense mutations may have a subtle effect in the retina. Furthermore, patients with mutations in CDH23 display a wide range of hearing loss and RP phenotypes, differing in severity, age at onset, type, and the presence or absence of vestibular areflexia.
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| 10. |
- Ralimanana, H., et al.
(författare)
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Madagascar’s extraordinary biodiversity: Threats and opportunities
- 2022
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 378:6623
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Forskningsöversikt (refereegranskat)abstract
- Madagascar’s unique biota is heavily affected by human activity and is under intense threat. Here, we review the current state of knowledge on the conservation status of Madagascar’s terrestrial and freshwater biodiversity by presenting data and analyses on documented and predicted species-level conservation statuses, the most prevalent and relevant threats, ex situ collections and programs, and the coverage and comprehensiveness of protected areas. The existing terrestrial protected area network in Madagascar covers 10.4% of its land area and includes at least part of the range of the majority of described native species of vertebrates with known distributions (97.1% of freshwater fishes, amphibians, reptiles, birds, and mammals combined) and plants (67.7%). The overall figures are higher for threatened species (97.7% of threatened vertebrates and 79.6% of threatened plants occurring within at least one protected area). International Union for Conservation of Nature (IUCN) Red List assessments and Bayesian neural network analyses for plants identify overexploitation of biological resources and unsustainable agriculture as the most prominent threats to biodiversity. We highlight five opportunities for action at multiple levels to ensure that conservation and ecological restoration objectives, programs, and activities take account of complex underlying and interacting factors and produce tangible benefits for the biodiversity and people of Madagascar.
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