scholarly journals Reliability of algorithmic somatic copy number alteration detection from targeted capture data

2017 ◽  
Vol 33 (18) ◽  
pp. 2791-2798 ◽  
Author(s):  
Nora Rieber ◽  
Regina Bohnert ◽  
Ulrike Ziehm ◽  
Gunther Jansen
Keyword(s):  
Copy Number ◽  
Copy Number Alteration ◽  
Targeted Capture ◽  
Somatic Copy Number Alteration

scholarly journals The landscape of somatic copy-number alteration across human cancers

Nature ◽  
2010 ◽  
Vol 463 (7283) ◽  
pp. 899-905 ◽  
Author(s):  
Rameen Beroukhim ◽  
Craig H. Mermel ◽  
Dale Porter ◽  
Guo Wei ◽  
Soumya Raychaudhuri ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Alteration ◽  
Human Cancers ◽  
Somatic Copy Number Alteration

scholarly journals GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers

2011 ◽  
Vol 12 (4) ◽  
Author(s):  
Craig H Mermel ◽  
Steven E Schumacher ◽  
Barbara Hill ◽  
Matthew L Meyerson ◽  
Rameen Beroukhim ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Alteration ◽  
Human Cancers ◽  
Somatic Copy Number Alteration

Genome-wide somatic copy number alteration analysis and database construction for cervical cancer

2020 ◽  
Vol 295 (3) ◽  
pp. 765-773 ◽  
Author(s):  
Hong Luo ◽  
Xiaohan Xu ◽  
Jian Yang ◽  
Kun Wang ◽  
Chen Wang ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Copy Number ◽  
Copy Number Alteration ◽  
Database Construction ◽  
Genome Wide ◽  
Somatic Copy Number Alteration

scholarly journals Identification of Tumor Mutation Burden, Microsatellite Instability, and Somatic Copy Number Alteration derived 9-gene Signatures to Predict Clinical Outcomes in STAD

2021 ◽  
Author(s):  
Chuanzhi Chen ◽  
Yi Chen ◽  
Xin Jin ◽  
Yongfeng Ding ◽  
Junjie Jiang ◽  
...  
Keyword(s):  
Microsatellite Instability ◽  
Copy Number ◽  
Copy Number Alteration ◽  
External Validation ◽  
The Cancer Genome Atlas ◽  
Roc Curve Analysis ◽  
Predictive Tool ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Somatic Copy Number Alteration

Abstract Background: Genomic features including tumor mutation burden (TMB), microsatellite instability (MSI) and somatic copy number alteration (SCNA), had been demonstrated to be involved with the tumor microenvironment (TME) and outcome of gastric cancer (GC). Methods: We obtained profiles of TMB, MSI and SCNA by processing 405 GC data from The Cancer Genome Atlas (TCGA), then conducted a comprehensive analysis though “iClusterPlus”. Another independent Gene Expression Omnibus (GEO) contained specimens from 109 GC patients was designed as an external validation. Results: Two subgroups were generated, with distinguished prognosis, somatic mutation burden, copy number changes and immune landscape. We revealed that Cluster1 was marked by a better prognosis, accompanied by higher TMB, MSIsensor score, TMEscore, and lower SCNA burden. Based on these clusters, we screened 196 differentially expressed genes (DEGs), which were subsequently projected into univariate Cox survival analysis. Thus, we constructed a 9-gene immune risk score (IRS) model using lasso penalized logistic regression. Moreover, the prognostic prediction of IRS was verified by receiver operating characteristic (ROC) curve analysis and nomogram plot.Conclusions: Our works suggested that the 9‐gene‐signature prediction model, which derived from TMB, MSI, SCNA was a promising predictive tool for clinical outcome in GC patients. This novel methodology may help clinicians uncover the underlying mechanisms and guide future treatment strategies.

scholarly journals DEFOR: depth- and frequency-based somatic copy number alteration detector

2019 ◽  
Vol 35 (19) ◽  
pp. 3824-3825 ◽  
Author(s):  
He Zhang ◽  
Xiaowei Zhan ◽  
James Brugarolas ◽  
Yang Xie
Keyword(s):  
Exome Sequencing ◽  
Copy Number ◽  
Copy Number Alteration ◽  
High Throughput Sequencing ◽  
Supplementary Information ◽  
Copy Number Alterations ◽  
Sequencing Data ◽  
Sequencing Technology ◽  
Somatic Copy Number Alterations ◽  
Somatic Copy Number Alteration

Abstract Motivation Detection of somatic copy number alterations (SCNAs) using high-throughput sequencing has become popular because of rapid developments in sequencing technology. Existing methods do not perform well in calling SCNAs for the unstable tumor genomes. Results We developed a new method, DEFOR, to detect SCNAs in tumor samples from exome-sequencing data. The evaluation showed that DEFOR has a higher accuracy for SCNA detection from exome sequencing compared with the five existing tools. This advantage is especially apparent in unstable tumor genomes with a large proportion of SCNAs. Availability and implementation DEFOR is available at https://github.com/drzh/defor. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals CNV Radar: an improved method for somatic copy number alteration characterization in oncology

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
David Soong ◽  
Jeran Stratford ◽  
Herve Avet-Loiseau ◽  
Nizar Bahlis ◽  
Faith Davies ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Alteration ◽  
Improved Method ◽  
Somatic Copy Number Alteration
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