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TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies
Mutational signatures are patterns of mutation types, many of which are linked to known mutagenic processes. Signature activity represents the proportion of mutations a signature generates. In cancer, cells may gain advantageous phenotypes through mutation accumulation, causing rapid growth of that...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6905203/ https://www.ncbi.nlm.nih.gov/pubmed/31797600 |
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author | Harrigan, Caitlin F Rubanova, Yulia Morris, Quaid Selega, Alina |
author_facet | Harrigan, Caitlin F Rubanova, Yulia Morris, Quaid Selega, Alina |
author_sort | Harrigan, Caitlin F |
collection | PubMed |
description | Mutational signatures are patterns of mutation types, many of which are linked to known mutagenic processes. Signature activity represents the proportion of mutations a signature generates. In cancer, cells may gain advantageous phenotypes through mutation accumulation, causing rapid growth of that subpopulation within the tumour. The presence of many subclones can make cancers harder to treat and have other clinical implications. Reconstructing changes in signature activities can give insight into the evolution of cells within a tumour. Recently, we introduced a new method, TrackSig, to detect changes in signature activities across time from single bulk tumour sample. By design, TrackSig is unable to identify mutation populations with different frequencies but little to no difference in signature activity. Here we present an extension of this method, TrackSigFreq, which enables trajectory reconstruction based on both observed density of mutation frequencies and changes in mutational signature activities. TrackSigFreq preserves the advantages of TrackSig, namely optimal and rapid mutation clustering through segmentation, while extending it so that it can identify distinct mutation populations that share similar signature activities. |
format | Online Article Text |
id | pubmed-6905203 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-69052032020-01-01 TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies Harrigan, Caitlin F Rubanova, Yulia Morris, Quaid Selega, Alina Pac Symp Biocomput Article Mutational signatures are patterns of mutation types, many of which are linked to known mutagenic processes. Signature activity represents the proportion of mutations a signature generates. In cancer, cells may gain advantageous phenotypes through mutation accumulation, causing rapid growth of that subpopulation within the tumour. The presence of many subclones can make cancers harder to treat and have other clinical implications. Reconstructing changes in signature activities can give insight into the evolution of cells within a tumour. Recently, we introduced a new method, TrackSig, to detect changes in signature activities across time from single bulk tumour sample. By design, TrackSig is unable to identify mutation populations with different frequencies but little to no difference in signature activity. Here we present an extension of this method, TrackSigFreq, which enables trajectory reconstruction based on both observed density of mutation frequencies and changes in mutational signature activities. TrackSigFreq preserves the advantages of TrackSig, namely optimal and rapid mutation clustering through segmentation, while extending it so that it can identify distinct mutation populations that share similar signature activities. 2020 /pmc/articles/PMC6905203/ /pubmed/31797600 Text en Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC) 4.0 License. http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Article Harrigan, Caitlin F Rubanova, Yulia Morris, Quaid Selega, Alina TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies |
title | TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies |
title_full | TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies |
title_fullStr | TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies |
title_full_unstemmed | TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies |
title_short | TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies |
title_sort | tracksigfreq: subclonal reconstructions based on mutation signatures and allele frequencies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6905203/ https://www.ncbi.nlm.nih.gov/pubmed/31797600 |
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