| 1. |
- Carraro, Marco, et al.
(författare)
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Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI
- 2017
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 38:9, s. 1042-1050
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Tidskriftsartikel (refereegranskat)abstract
- Correct phenotypic interpretation of variants of unknown significance for cancer-associated genes is a diagnostic challenge as genetic screenings gain in popularity in the next-generation sequencing era. The Critical Assessment of Genome Interpretation (CAGI) experiment aims to test and define the state of the art of genotype-phenotype interpretation. Here, we present the assessment of the CAGI p16INK4a challenge. Participants were asked to predict the effect on cellular proliferation of 10 variants for the p16INK4a tumor suppressor, a cyclin-dependent kinase inhibitor encoded by the CDKN2A gene. Twenty-two pathogenicity predictors were assessed with a variety of accuracy measures for reliability in a medical context. Different assessment measures were combined in an overall ranking to provide more robust results. The R scripts used for assessment are publicly available from a GitHub repository for future use in similar assessment exercises. Despite a limited test-set size, our findings show a variety of results, with some methods performing significantly better. Methods combining different strategies frequently outperform simpler approaches. The best predictor, Yang&Zhou lab, uses a machine learning method combining an empirical energy function measuring protein stability with an evolutionary conservation term. The p16INK4a challenge highlights how subtle structural effects can neutralize otherwise deleterious variants.
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| 2. |
- Daneshjou, Roxana, et al.
(författare)
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Working toward precision medicine : Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges
- 2017
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 38:9, s. 1182-1192
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Tidskriftsartikel (refereegranskat)abstract
- Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships.
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| 3. |
- Ekong, Rosemary, et al.
(författare)
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Checklist for gene/disease-specific variation database curators to enable ethical data management
- 2019
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 40:10, s. 1634-1640
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Tidskriftsartikel (refereegranskat)abstract
- Databases with variant and phenotype information are essential for advancing research and improving the health and welfare of individuals. These resources require data to be collected, curated, and shared among relevant specialties to maximize impact. The increasing generation of data which must be shared both nationally and globally for maximal effect presents important ethical and privacy concerns. Database curators need to ensure that their work conform to acceptable ethical standards. A Working Group of the Human Variome Project had the task of updating and streamlining ethical guidelines for locus-specific/gene variant database curators. In this article, we present practical and achievable steps which should assist database curators in carrying out their responsibilities within acceptable ethical norms.
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| 4. |
- Niroula, Abhishek, et al.
(författare)
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PON-P and PON-P2 predictor performance in CAGI challenges : Lessons learned
- 2017
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 38:9, s. 1085-1091
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Tidskriftsartikel (refereegranskat)abstract
- Computational tools are widely used for ranking and prioritizing variants for characterizing their disease relevance. Since numerous tools have been developed, they have to be properly assessed before being applied. Critical Assessment of Genome Interpretation (CAGI) experiments have significantly contributed toward the assessment of prediction methods for various tasks. Within and outside the CAGI, we have addressed several questions that facilitate development and assessment of variation interpretation tools. These areas include collection and distribution of benchmark datasets, their use for systematic large-scale method assessment, and the development of guidelines for reporting methods and their performance. For us, CAGI has provided a chance to experiment with new ideas, test the application areas of our methods, and network with other prediction method developers. In this article, we discuss our experiences and lessons learned from the various CAGI challenges. We describe our approaches, their performance, and impact of CAGI on our research. Finally, we discuss some of the possibilities that CAGI experiments have opened up and make some suggestions for future experiments.
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| 5. |
- Valiaho, Jouni, et al.
(författare)
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Characterization of All Possible Single-Nucleotide Change Caused Amino Acid Substitutions in the Kinase Domain of Bruton Tyrosine Kinase
- 2015
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 36:6, s. 638-647
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge about features distinguishing deleterious and neutral variations is crucial for interpretation of novel variants. Bruton tyrosine kinase (BTK) contains the highest number of unique disease-causing variations among the human protein kinases, still it is just 10% of all the possible single-nucleotide substitution-caused amino acid variations (SNAVs). In the BTK kinase domain (BTK-KD) can appear altogether 1,495 SNAVs. We investigated them all with bioinformatic and protein structure analysis methods. Most disease-causing variations affect conserved and buried residues disturbing protein stability. Minority of exposed residues is conserved, but strongly tied to pathogenicity. Sixty-seven percent of variations are predicted to be harmful. In 39% of the residues, all the variants are likely harmful, whereas in 10% of sites, all the substitutions are tolerated. Results indicate the importance of the entire kinase domain, involvement in numerous interactions, and intricate functional regulation by conformational change. These results can be extended to other protein kinases and organisms.
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| 6. |
- Ali, Heidi, et al.
(författare)
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Classification of mismatch repair gene missense variants with PON-MMR
- 2012
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794. ; 33:4, s. 642-650
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Tidskriftsartikel (refereegranskat)abstract
- Numerous mismatch repair (MMR) gene variants have been identified in Lynch syndrome and other cancer patients, but knowledge about their pathogenicity is frequently missing. The diagnosis and treatment of patients would benefit from knowing which variants are disease related. Bioinformatic approaches are well suited to the problem and can handle large numbers of cases. Functional effects were revealed based on literature for 168 MMR missense variants. Performance of numerous prediction methods was tested with this dataset. Among the tested tools, only the results of tolerance prediction methods correlated to functional information, however, with poor performance. Therefore, a novel consensus-based predictor was developed. The novel prediction method, pathogenic-or-not mismatch repair (PON-MMR), achieved accuracy of 0.87 and Matthews correlation coefficient of 0.77 on the experimentally verified variants. When applied to 616 MMR cases with unknown effects, 81 missense variants were predicted to be pathogenic and 167 neutral. With PON-MMR, the number of MMR missense variants with unknown effect was reduced by classifying a large number of cases as likely pathogenic or benign. The results can be used, for example, to prioritize cases for experimental studies and assist in the classification of cases. Hum Mutat 33:642650, 2012. (c) 2012 Wiley Periodicals, Inc.
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| 7. |
- Ali, Heidi, et al.
(författare)
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Performance of Protein Disorder Prediction Programs on Amino Acid Substitutions
- 2014
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794. ; 35:7, s. 794-804
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Forskningsöversikt (refereegranskat)abstract
- Many proteins contain intrinsically disordered regions, which may be crucial for function, but on the other hand be related to the pathogenicity of variants. Prediction programs have been developed to detect disordered regions from sequences and used to predict the consequences of variants, although their performance for this task has not been assessed. We tested the performance of protein disorder prediction programs in detecting changes to disorder caused by amino acid substitutions. We assessed the performance of 29 protein disorder predictors and versions with 101 amino acid substitutions, whose effects have been experimentally validated. Disorder predictors detected the true positives at most with 6% success rate and true negatives with 34% rate for variants. The corresponding rates for the wild-type forms are 7% and 90%, respectively. The analysis revealed that disorder programs cannot reliably predict the effects of substitutions; consequently, the tested methods, and possibly similar programs, cannot be recommended for variant analysis without other information indicating to the relevance of disorder. These results inspired us to develop a new method, PON-Diso (http://structure.bmc.lu.se/PON-Diso), for disorder-related amino acid substitutions. With 50% success rate for independent test set and 70.5% rate in cross-validation, it outperforms the evaluated methods.
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| 8. |
- Nair, Preethy Sasidharan, et al.
(författare)
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VariBench: A Benchmark Database for Variations
- 2013
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794. ; 34:1, s. 42-49
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Tidskriftsartikel (refereegranskat)abstract
- Several computational methods have been developed for predicting the effects of rapidly expanding variation data. Comparison of the performance of tools has been very difficult as the methods have been trained and tested with different datasets. Until now, unbiased and representative benchmark datasets have been missing. We have developed a benchmark database suite, VariBench, to overcome this problem. VariBench contains datasets of experimentally verified high-quality variation data carefully chosen from literature and relevant databases. It provides the mapping of variation position to different levels (protein, RNA and DNA sequences, protein three-dimensional structure), along with identifier mapping to relevant databases. VariBench contains the first benchmark datasets for variation effect analysis, a field which is of high importance and where many developments are currently going on. VariBench datasets can be used, for example, to test performance of prediction tools as well as to train novel machine learning-based tools. New datasets will be included and the community is encouraged to submit high-quality datasets to the service. VariBench is freely available at http://structure.bmc.lu.se/VariBench. Hum Mutat 34:42-49, 2013. (C) 2012 Wiley Periodicals, Inc.
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| 9. |
- Niroula, Abhishek, et al.
(författare)
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Classification of Amino Acid Substitutions in Mismatch Repair Proteins Using PON-MMR2.
- 2015
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794. ; 36:12, s. 1128-1134
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Tidskriftsartikel (refereegranskat)abstract
- Variations in mismatch repair (MMR) system genes are causative of Lynch syndrome and other cancers. Thousands of variants have been identified in MMR genes, but the clinical relevance is known for only a small proportion. Recently, the InSiGHT group classified 2,360 MMR variants into five classes. One-third of variants, majority of which is nonsynonymous variants, remain to be of uncertain clinical relevance. Computational tools can be used to prioritize variants for disease relevance investigations. Previously, we classified 248 MMR variants as likely pathogenic and likely benign using PON-MMR. We have developed a novel tool, PON-MMR2, which is trained on a larger and more reliable dataset. In performance comparison, PON-MMR2 outperforms both generic tolerance prediction methods as well as methods optimized for MMR variants. It achieves accuracy and MCC of 0.89 and 0.78, respectively, in cross-validation and 0.86 and 0.69, respectively, on an independent test dataset. We classified 354 class 3 variants in InSiGHT database as well as all possible amino acid substitutions in four MMR proteins. Likely harmful variants mainly appear in the protein core, whereas likely benign variants are on the surface. PON-MMR2 is a highly reliable tool to prioritize variants for functional analysis. It is freely available at http://structure.bmc.lu.se/PON-MMR2/.
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| 10. |
- Niroula, Abhishek, et al.
(författare)
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Variation Interpretation Predictors : Principles, Types, Performance, and Choice
- 2016
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794. ; 37:6, s. 579-597
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Tidskriftsartikel (refereegranskat)abstract
- Next-generation sequencing methods have revolutionized the speed of generating variation information. Sequence data have a plethora of applications and will increasingly be used for disease diagnosis. Interpretation of the identified variants is usually not possible with experimental methods. This has caused a bottleneck that many computational methods aim at addressing. Fast and efficient methods for explaining the significance and mechanisms of detected variants are required for efficient precision/personalized medicine. Computational prediction methods have been developed in three areas to address the issue. There are generic tolerance (pathogenicity) predictors for filtering harmful variants. Gene/protein/disease-specific tools are available for some applications. Mechanism and effect-specific computer programs aim at explaining the consequences of variations. Here, we discuss the different types of predictors and their applications. We review available variation databases and prediction methods useful for variation interpretation. We discuss how the performance of methods is assessed and summarize existing assessment studies. A brief introduction is provided to the principles of the methods developed for variation interpretation as well as guidelines for how to choose the optimal tools and where the field is heading in the future.
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