Motivation: Despite widespread prevalence of somatic structural variations (SVs) across most tumor types, understanding of their molecular implications often remains poor. SVs are extremely heterogeneous in size and complexity, hindering the interpretation of their pathogenic role. Tools integrating large SV datasets across platforms are required to fully characterize the cancer's somatic landscape. Results: svpluscnv R package is a swiss army knife for the integration and interpretation of orthogonal datasets including copy number variant segmentation profiles and sequencing-based structural variant calls. The package implements analysis and visualization tools to evaluate chromosomal instability and ploidy, identify genes harboring recurrent SVs and detects complex rearrangements such as chromothripsis and chromoplexia. Further, it allows systematic identification of hot-spot shattered genomic regions, showing reproducibility across alternative detection methods and datasets.
Lopez G., Egolf L.E., Giorgi F.M., Diskin S.J., Margolin A.A. (2021). Svpluscnv: Analysis and visualization of complex structural variation data. BIOINFORMATICS, 37(13), 1912-1914 [10.1093/bioinformatics/btaa878].
Svpluscnv: Analysis and visualization of complex structural variation data
Giorgi F. M.;
2021
Abstract
Motivation: Despite widespread prevalence of somatic structural variations (SVs) across most tumor types, understanding of their molecular implications often remains poor. SVs are extremely heterogeneous in size and complexity, hindering the interpretation of their pathogenic role. Tools integrating large SV datasets across platforms are required to fully characterize the cancer's somatic landscape. Results: svpluscnv R package is a swiss army knife for the integration and interpretation of orthogonal datasets including copy number variant segmentation profiles and sequencing-based structural variant calls. The package implements analysis and visualization tools to evaluate chromosomal instability and ploidy, identify genes harboring recurrent SVs and detects complex rearrangements such as chromothripsis and chromoplexia. Further, it allows systematic identification of hot-spot shattered genomic regions, showing reproducibility across alternative detection methods and datasets.File | Dimensione | Formato | |
---|---|---|---|
Svpluscnv et al..pdf
accesso aperto
Tipo:
Versione (PDF) editoriale
Licenza:
Licenza per Accesso Aperto. Altra tipologia di licenza compatibile con Open Access
Dimensione
5.16 MB
Formato
Adobe PDF
|
5.16 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.