Could Dystonia Be Initial Presentation of Corpus Callosum Infarction in Young Age Patients? A Case Report Study

Ibrahim, Mohamed Hamdy; Fadhil, Alyaa; Ali, Sameh Saied; Kader, Salma Fathy Abdel; Kumar, K. S. Kavi; Kumar, Shivram; Sirsat, Janhavi

doi:10.4236/nm.2015.62011

Cited by 2 publications

(1 citation statement)

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“…The same analysis identified Writer's cramp (HP: 0002356; P < 1.37 × 10 −9 ) as exclusive to EOD and this refers to a type of focal dystonia [ 57 ]. We also found Hypoplasia of the corpus callosum (HP: 0002079; P < 3.56 × 10 −5 ), a controversial and not widely studied phenotype in dystonia [ 58 , 59 ] and Acanthocytosis (HP: 0001927; P < 2.76 × 10 −3 ) a term normally associated with chorea‐acanthocytosis, other disease with dystonia’s similar symptoms [ 60 ]. Microcephaly (HP: 0000252; P < 4.17 × 10 −4 ) is associated with dystonia and several genes such as KMT2B [ 61 , 62 ].…”

Section: Resultsmentioning

confidence: 90%

PhenoExam: gene set analyses through integration of different phenotype databases

et al. 2022

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Background Gene set enrichment analysis (detecting phenotypic terms that emerge as significant in a set of genes) plays an important role in bioinformatics focused on diseases of genetic basis. To facilitate phenotype-oriented gene set analysis, we developed PhenoExam, a freely available R package for tool developers and a web interface for users, which performs: (1) phenotype and disease enrichment analysis on a gene set; (2) measures statistically significant phenotype similarities between gene sets and (3) detects significant differential phenotypes or disease terms across different databases. Results PhenoExam generates sensitive and accurate phenotype enrichment analyses. It is also effective in segregating gene sets or Mendelian diseases with very similar phenotypes. We tested the tool with two similar diseases (Parkinson and dystonia), to show phenotype-level similarities but also potentially interesting differences. Moreover, we used PhenoExam to validate computationally predicted new genes potentially associated with epilepsy. Conclusions We developed PhenoExam, a freely available R package and Web application, which performs phenotype enrichment and disease enrichment analysis on gene set G, measures statistically significant phenotype similarities between pairs of gene sets G and G′ and detects statistically significant exclusive phenotypes or disease terms, across different databases. We proved with simulations and real cases that it is useful to distinguish between gene sets or diseases with very similar phenotypes. Github R package URL is https://github.com/alexcis95/PhenoExam. Shiny App URL is https://alejandrocisterna.shinyapps.io/phenoexamweb/.

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Section: Resultsmentioning

confidence: 90%

PhenoExam: gene set analyses through integration of different phenotype databases

et al. 2022

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PhenoExam: an R package and Web application for the examination of phenotypes linked to genes and gene sets

Cisterna-García

González-Vidal

Villa

et al. 2021

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Gene set based phenotype enrichment analysis (detecting phenotypic terms that emerge as significant in a set of genes) can improve the rate of genetic diagnoses amongst other research purposes. To facilitate diverse phenotype analysis, we developed PhenoExam, a freely available R package for tool developers and a web interface for users, which performs: (1) phenotype and disease enrichment analysis on a gene set; (2) measures statistically significant phenotype similarities between gene sets and (3) detects significant differential phenotypes or disease terms across different databases. PhenoExam achieves these tasks by integrating databases or resources such as the HPO, MGD, CRISPRbrain, CTD, ClinGen, CGI, OrphaNET, UniProt, PsyGeNET, and Genomics England Panel App. PhenoExam accepts both human and mouse genes as input. We developed PhenoExam to assist a variety of users, including clinicians, computational biologists and geneticists. It can be used to support the validation of new gene-to-disease discoveries, and in the detection of differential phenotypes between two gene sets (a phenotype linked to one of the gene set but no to the other) that are useful for differential diagnosis and to improve genetic panels. We validated PhenoExam performance through simulations and its application to real cases. We demonstrate that PhenoExam is effective in distinguishing gene sets or Mendelian diseases with very similar phenotypes through projecting the disease-causing genes into their annotation-based phenotypic spaces. We also tested the tool with early onset Parkinson's disease and dystonia genes, to show phenotype-level similarities but also potentially interesting differences. More specifically, we used PhenoExam to validate computationally predicted new genes potentially associated with epilepsy. Therefore, PhenoExam effectively discovers links between phenotypic terms across annotation databases through effective integration. The R package is available at https://github.com/alexcis95/PhenoExam and the Web tool is accessible at https://snca.atica.um.es/PhenoExamWeb/.

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Could Dystonia Be Initial Presentation of Corpus Callosum Infarction in Young Age Patients? A Case Report Study

Cited by 2 publications

References 12 publications

PhenoExam: gene set analyses through integration of different phenotype databases

PhenoExam: gene set analyses through integration of different phenotype databases

PhenoExam: an R package and Web application for the examination of phenotypes linked to genes and gene sets

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