2014
DOI: 10.1186/preaccept-1691129011290725
|View full text |Cite
|
Sign up to set email alerts
|

SubcloneSeeker: a computational framework for reconstructing tumor clone structure for cancer variant interpretation and prioritization

Abstract: Many tumors are composed of genetically divergent cell subpopulations. We report SubcloneSeeker, a package capable of exhaustive identification of subclone structures and evolutionary histories with bulk somatic variant allele frequency measurements from tumor biopsies. We present a statistical framework to elucidate whether specific sets of mutations are present within the same subclones, and the order in which they occur. We demonstrate how subclone reconstruction provides crucial information about tumorigen… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
31
0

Year Published

2014
2014
2021
2021

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 18 publications
(31 citation statements)
references
References 47 publications
0
31
0
Order By: Relevance
“…[43]. Cancer cell fractions were defined using ABSOLUTE [44] and clonal composition analysis was carried out using SubcloneSeeker [45] (Supplementary Methods). …”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…[43]. Cancer cell fractions were defined using ABSOLUTE [44] and clonal composition analysis was carried out using SubcloneSeeker [45] (Supplementary Methods). …”
Section: Methodsmentioning
confidence: 99%
“…Red solid arrows depict the divergence of a cell population from one lesion to another. Decomposition of genetically distinct clones and clonal evolution in lesions from case 9 and case 16 were performed using the results from ABSOLUTE [44] and SubcloneSeeker [45]. The percentages indicate the prevalence of each clone in each morphologically distinct component of each case.…”
Section: Figurementioning
confidence: 99%
“…Given the variations in the rates and mechanisms of SNV versus CNV evolution, some methods have found particular power in combining data types, as is done by GRAFT 134 , PhyloWGS 135 , SPRUCE 136 , and Canopy 137 . The available methods also cover a range of models and algorithmic techniques, including various combinatorial (parsimony-like) character-based methods 130,131,134,138 , probabilistic character-based methods 133,135 , and distance-based minimum evolution 85 .…”
Section: Variations On Tumour Phylogeneticsmentioning
confidence: 99%
“…These encompass next-generation sequencing methods for analyzing tumor and normal cell composition, the analysis of clonal populations in cancers (Qiao et al . [ 6 ]), and methods addressing epigenetic plasticity (Zheng et al . [ 7 ]).…”
Section: Methodological Approaches To Heterogeneitymentioning
confidence: 99%