OncodriveCLUST

OncodriveCLUST is a method aimed to identify genes whose mutations are biased towards a large spatial clustering. This method is designed to exploit the feature that mutations in cancer genes, especially oncogenes, often cluster in particular positions of the protein. We consider this as a sign that...

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Detalhes bibliográficos
Autores: Tamborero Noguera, David, González-Pérez, Abel, López Bigas, Núria
Tipo de documento: conjunto de datos
Data de publicação:2023
País:España
Recursos:Consorci de Serveis Universitaris de Catalunya (CSUC)
Repositório:CORA.Repositori de Dades de Recerca
OAI Identifier:oai:dnet:cora.rdr____::82a4b77a7577f374f6594688e71d807b
Acesso em linha:https://doi.org/10.34810/DATA412
Access Level:Acceso aberto
Palavra-chave:Medicine, Health and Life Sciences
Cancer
Genes
Mutation
Clustering
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repository_id_str
spelling OncodriveCLUSTTamborero Noguera, DavidGonzález-Pérez, AbelLópez Bigas, NúriaMedicine, Health and Life SciencesCancerGenesMutationClusteringOncodriveCLUST is a method aimed to identify genes whose mutations are biased towards a large spatial clustering. This method is designed to exploit the feature that mutations in cancer genes, especially oncogenes, often cluster in particular positions of the protein. We consider this as a sign that mutations in these regions change the function of these proteins in a manner that provides an adaptive advantage to cancer cells and consequently are positively selected during clonal evolution of tumours, and this property can thus be used to nominate novel candidate driver genes./nThe method does not assume that the baseline mutation probability is homogeneous across all gene positions but it creates a background model using silent mutations. Coding silent mutations are supposed to be under no positive selection and may reflect the baseline clustering of somatic mutations. Given recent evidences of non-random mutation processes along the genome, the assumption of homogenous mutation probabilities is likely an oversimplication introducing bias in the detection of meaningful events.CORA.Repositori de Dades de Recerca2023info:eu-repo/semantics/datasethttps://doi.org/10.34810/DATA412reponame:CORA.Repositori de Dades de Recercainstname:Consorci de Serveis Universitaris de Catalunya (CSUC)Inglésinfo:eu-repo/semantics/openAccessCustom Dataset Termsoai:dnet:cora.rdr____::82a4b77a7577f374f6594688e71d807b2026-06-17T12:20:17Z
dc.title.none.fl_str_mv OncodriveCLUST
title OncodriveCLUST
spellingShingle OncodriveCLUST
Tamborero Noguera, David
Medicine, Health and Life Sciences
Cancer
Genes
Mutation
Clustering
title_short OncodriveCLUST
title_full OncodriveCLUST
title_fullStr OncodriveCLUST
title_full_unstemmed OncodriveCLUST
title_sort OncodriveCLUST
dc.creator.none.fl_str_mv Tamborero Noguera, David
González-Pérez, Abel
López Bigas, Núria
author Tamborero Noguera, David
author_facet Tamborero Noguera, David
González-Pérez, Abel
López Bigas, Núria
author_role author
author2 González-Pérez, Abel
López Bigas, Núria
author2_role author
author
dc.subject.none.fl_str_mv Medicine, Health and Life Sciences
Cancer
Genes
Mutation
Clustering
topic Medicine, Health and Life Sciences
Cancer
Genes
Mutation
Clustering
description OncodriveCLUST is a method aimed to identify genes whose mutations are biased towards a large spatial clustering. This method is designed to exploit the feature that mutations in cancer genes, especially oncogenes, often cluster in particular positions of the protein. We consider this as a sign that mutations in these regions change the function of these proteins in a manner that provides an adaptive advantage to cancer cells and consequently are positively selected during clonal evolution of tumours, and this property can thus be used to nominate novel candidate driver genes./nThe method does not assume that the baseline mutation probability is homogeneous across all gene positions but it creates a background model using silent mutations. Coding silent mutations are supposed to be under no positive selection and may reflect the baseline clustering of somatic mutations. Given recent evidences of non-random mutation processes along the genome, the assumption of homogenous mutation probabilities is likely an oversimplication introducing bias in the detection of meaningful events.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/dataset
format dataset
dc.identifier.none.fl_str_mv https://doi.org/10.34810/DATA412
url https://doi.org/10.34810/DATA412
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Custom Dataset Terms
eu_rights_str_mv openAccess
rights_invalid_str_mv Custom Dataset Terms
dc.publisher.none.fl_str_mv CORA.Repositori de Dades de Recerca
publisher.none.fl_str_mv CORA.Repositori de Dades de Recerca
dc.source.none.fl_str_mv reponame:CORA.Repositori de Dades de Recerca
instname:Consorci de Serveis Universitaris de Catalunya (CSUC)
instname_str Consorci de Serveis Universitaris de Catalunya (CSUC)
reponame_str CORA.Repositori de Dades de Recerca
collection CORA.Repositori de Dades de Recerca
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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