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Sub-GOFA: A tool for Sub-Gene Ontology function analysis in clonal mosaicism using semantic (logical) similarity

Clonal mosaicism (a detectable post-zygotic mutational event in cellular subpopulations) is common in cancer patients. Detected segments of clonal mosaicism are usually bundled into large-locus regions for statistical analysis. However, low-frequency genes are overlooked and are not sufficient to el...

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Detalles Bibliográficos
Autores principales: Katsuda, Tadaaki, Sato, Noriko, Mogushi, Kaoru, Hase, Takeshi, Muramatsu, Masaaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200605/
https://www.ncbi.nlm.nih.gov/pubmed/35815201
http://dx.doi.org/10.6026/97320630018053
Descripción
Sumario:Clonal mosaicism (a detectable post-zygotic mutational event in cellular subpopulations) is common in cancer patients. Detected segments of clonal mosaicism are usually bundled into large-locus regions for statistical analysis. However, low-frequency genes are overlooked and are not sufficient to elucidate qualitative differences between cancer patients and non-patients. Therefore, it is of interest to develop and describe a tool named Sub-GOFA for Sub-Gene Ontology function analysis in clonal mosaicism using semantic similarity. Sub-GOFA measures the semantic (logical) similarity among patients using the sub-GO network structures of various sizes segmented from the gene ontology (GO) for clustering analysis. The sub-GO's root-terms with significant differences are extracted as disease-associated genetic functions. Sub-GOFA selected a high ratio of cancer-associated genes under validation with acceptable threshold.