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Dataset of tugHall simulations of cell evolution for colorectal cancer
Dataset contains results of multiple parallel calculations using the tugHall simulator. Output data of simulations are variant allele frequencies for four genes (APC, KRAS, TP53, and PIK3CA) related to colorectal cancer. During each simulation tugHall stochastically reproduces Darwinian evolution fo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820384/ https://www.ncbi.nlm.nih.gov/pubmed/33521175 http://dx.doi.org/10.1016/j.dib.2021.106719 |
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author | Nagornov, Iurii S. Nishino, Jo Kato, Mamoru |
author_facet | Nagornov, Iurii S. Nishino, Jo Kato, Mamoru |
author_sort | Nagornov, Iurii S. |
collection | PubMed |
description | Dataset contains results of multiple parallel calculations using the tugHall simulator. Output data of simulations are variant allele frequencies for four genes (APC, KRAS, TP53, and PIK3CA) related to colorectal cancer. During each simulation tugHall stochastically reproduces Darwinian evolution for cancer cells and calculates clonal heterogeneity. The probabilities of stochastic processes depend on a correspondence matrix between genome information and cancer hallmarks. As a result, tugHall records variant allele frequencies for the final stage of evolution. The number of trials is several million to get rich statistics of stochastic processes. These data can be used for approximate Bayesian computation and other statistical methods to get personalized coefficients for patients with colorectal cancer. The procedure of usage data is explained in our paper [Bioinformatics, 36, 11 (2020) 3597] in which the part of these data was used. |
format | Online Article Text |
id | pubmed-7820384 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-78203842021-01-29 Dataset of tugHall simulations of cell evolution for colorectal cancer Nagornov, Iurii S. Nishino, Jo Kato, Mamoru Data Brief Data Article Dataset contains results of multiple parallel calculations using the tugHall simulator. Output data of simulations are variant allele frequencies for four genes (APC, KRAS, TP53, and PIK3CA) related to colorectal cancer. During each simulation tugHall stochastically reproduces Darwinian evolution for cancer cells and calculates clonal heterogeneity. The probabilities of stochastic processes depend on a correspondence matrix between genome information and cancer hallmarks. As a result, tugHall records variant allele frequencies for the final stage of evolution. The number of trials is several million to get rich statistics of stochastic processes. These data can be used for approximate Bayesian computation and other statistical methods to get personalized coefficients for patients with colorectal cancer. The procedure of usage data is explained in our paper [Bioinformatics, 36, 11 (2020) 3597] in which the part of these data was used. Elsevier 2021-01-11 /pmc/articles/PMC7820384/ /pubmed/33521175 http://dx.doi.org/10.1016/j.dib.2021.106719 Text en © 2021 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Nagornov, Iurii S. Nishino, Jo Kato, Mamoru Dataset of tugHall simulations of cell evolution for colorectal cancer |
title | Dataset of tugHall simulations of cell evolution for colorectal cancer |
title_full | Dataset of tugHall simulations of cell evolution for colorectal cancer |
title_fullStr | Dataset of tugHall simulations of cell evolution for colorectal cancer |
title_full_unstemmed | Dataset of tugHall simulations of cell evolution for colorectal cancer |
title_short | Dataset of tugHall simulations of cell evolution for colorectal cancer |
title_sort | dataset of tughall simulations of cell evolution for colorectal cancer |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820384/ https://www.ncbi.nlm.nih.gov/pubmed/33521175 http://dx.doi.org/10.1016/j.dib.2021.106719 |
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