
Biological Psychiatry, Год журнала: 2019, Номер 87(2), С. 100 - 112
Опубликована: Июнь 29, 2019
Язык: Английский
Biological Psychiatry, Год журнала: 2019, Номер 87(2), С. 100 - 112
Опубликована: Июнь 29, 2019
Язык: Английский
The American Journal of Human Genetics, Год журнала: 2022, Номер 109(12), С. 2163 - 2177
Опубликована: Ноя. 21, 2022
Recommendations from the American College of Medical Genetics and Genomics Association for Molecular Pathology (ACMG/AMP) interpreting sequence variants specify use computational predictors as "supporting" level evidence pathogenicity or benignity using criteria PP3 BP4, respectively. However, score intervals defined by tool developers, ACMG/AMP recommendations that require consensus multiple predictors, lack quantitative support. Previously, we described a probabilistic framework quantified strengths (supporting, moderate, strong, very strong) within recommendations. We have extended this to introduce new standard converts tool's scores BP4 strengths. Our approach is based on estimating local positive predictive value can calibrate any other continuous-scale variant type. estimate thresholds (score intervals) corresponding each strength thirteen missense interpretation tools, carefully assembled independent data sets. Most tools achieved supporting both pathogenic benign classification newly established thresholds. Multiple reached justifying moderate several strong levels. One some variants. Based these findings, provide evidence-based revisions individual future assessment methods clinical interpretation.
Язык: Английский
Процитировано
287Annual Review of Public Health, Год журнала: 2017, Номер 39(1), С. 95 - 112
Опубликована: Дек. 20, 2017
The digital world is generating data at a staggering and still increasing rate. While these “big data” have unlocked novel opportunities to understand public health, they hold greater potential for research practice. This review explores several key issues that arisen around big data. First, we propose taxonomy of sources clarify terminology identify threads common across some subtypes Next, consider health practice uses data, including surveillance, hypothesis-generating research, causal inference, while exploring the role machine learning may play in each use. We then ethical implications revolution with particular emphasis on maintaining appropriate care privacy which technology rapidly changing social norms regarding need (and even meaning of) privacy. Finally, make suggestions structuring teams training succeed working
Язык: Английский
Процитировано
285Genome Medicine, Год журнала: 2022, Номер 14(1)
Опубликована: Окт. 8, 2022
Multiple computational approaches have been developed to improve our understanding of genetic variants. However, their ability identify rare pathogenic variants from benign ones is still lacking. Using context annotations and deep learning methods, we present pathogenicity prediction models, MetaRNN MetaRNN-indel, help prioritize nonsynonymous single nucleotide (nsSNVs) non-frameshift insertion/deletions (nfINDELs). We use independent test sets demonstrate that these new models outperform state-of-the-art competitors achieve a more interpretable score distribution. Importantly, scores both are comparable, enabling easy adoption integrated genotype-phenotype association analysis methods. All pre-computed nsSNV available at http://www.liulab.science/MetaRNN . The stand-alone program also https://github.com/Chang-Li2019/MetaRNN
Язык: Английский
Процитировано
100Journal of Evolutionary Biology, Год журнала: 2023, Номер 36(12), С. 1761 - 1782
Опубликована: Ноя. 9, 2023
Abstract Inversions are structural mutations that reverse the sequence of a chromosome segment and reduce effective rate recombination in heterozygous state. They play major role adaptation, as well other evolutionary processes such speciation. Although inversions have been studied since 1920s, they remain difficult to investigate because reduced conferred by them strengthens effects drift hitchhiking, which turn can obscure signatures selection. Nonetheless, numerous found be under Given recent advances population genetic theory empirical study, here we review how different mechanisms selection affect evolution inversions. A key difference between mutations, single nucleotide variants, is fitness an inversion may affected larger number frequently interacting processes. This considerably complicates analysis causes underlying We discuss extent these disentangled, approach. often roles adaptation speciation, but direct their obscured characteristic makes so unique (reduced arrangements). In this review, examine impact evolution, weaving together both theoretical studies. emphasize most patterns overdetermined (i.e. caused multiple processes), highlight new technologies provide path forward towards disentangling mechanisms.
Язык: Английский
Процитировано
48Genome biology, Год журнала: 2024, Номер 25(1)
Опубликована: Фев. 22, 2024
Abstract Background The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction genetic variant impact, particularly where relevant disease. five complete editions CAGI community experiment comprised 50 challenges, in which participants made blind predictions phenotypes from data, and these were evaluated by independent assessors. Results Performance was strong clinical pathogenic variants, including some difficult-to-diagnose cases, extends interpretation cancer-related variants. Missense methods able estimate biochemical effects with increasing accuracy. regulatory variants complex trait disease risk less definitive indicates performance potentially suitable auxiliary use clinic. Conclusions show that while current are imperfect, they have major utility research applications. Emerging increasingly large, robust datasets training assessment promise further progress ahead.
Язык: Английский
Процитировано
37Protein Science, Год журнала: 2019, Номер 29(1), С. 111 - 119
Опубликована: Окт. 13, 2019
VarSite is a web server mapping known disease-associated variants from UniProt and ClinVar, together with natural gnomAD, onto protein 3D structures in the Protein Data Bank. The analyses are primarily image-based provide both an overview for each human protein, as well report any specific variant of interest. information can be useful assessing whether given might pathogenic or benign. structural annotations position include secondary structure, interactions ligand, metal, DNA/RNA, other various measures variant's possible impact on protein's function. locations viewed interactively via 3dmol.js JavaScript viewer, RasMol PyMOL. Users search variants, sets by providing DNA coordinates base change(s) Additionally, agglomerative given, such disease Pfam CATH domains. freely accessible to all at: https://www.ebi.ac.uk/thornton-srv/databases/VarSite.
Язык: Английский
Процитировано
103Nature Medicine, Год журнала: 2019, Номер 26(1), С. 143 - 150
Опубликована: Дек. 23, 2019
Язык: Английский
Процитировано
93Sustainable Cities and Society, Год журнала: 2020, Номер 63, С. 102466 - 102466
Опубликована: Авг. 28, 2020
Язык: Английский
Процитировано
92The Plant Journal, Год журнала: 2022, Номер 111(6), С. 1527 - 1538
Опубликована: Июль 13, 2022
SUMMARY Advances in high‐throughput omics technologies are leading plant biology research into the era of big data. Machine learning (ML) performs an important role systems because its excellent performance and wide application analysis However, to achieve ideal performance, supervised ML algorithms require large numbers labeled samples as training In some cases, it is impossible or prohibitively expensive obtain enough data; here, paradigms unsupervised (UL) semi‐supervised (SSL) play indispensable role. this review, we first introduce basic concepts techniques, well representative UL SSL algorithms, including clustering, dimensionality reduction, self‐supervised (self‐SL), positive‐unlabeled (PU) transfer learning. We then review recent advances applications both phenotyping research. Finally, discuss limitations highlight significance challenges strategies biology.
Язык: Английский
Процитировано
61Frontiers in Genetics, Год журнала: 2022, Номер 13
Опубликована: Ноя. 29, 2022
Molecular biology is currently a fast-advancing science. Sequencing techniques are getting cheaper, but the interpretation of genetic variants requires expertise and computational power, therefore still challenge. Next-generation sequencing releases thousands to classify them, researchers propose protocols with several parameters. Here we present review in silico pathogenicity prediction tools involved variant prioritization/classification process used by some international for analysis studies evaluating their efficiency.
Язык: Английский
Процитировано
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