ERDS-pe: A paired hidden Markov model for copy number variant detection from whole-exome sequencing data

2016 ◽  
Author(s):  
Renjie Tan ◽  
Jixuan Wang ◽  
Xiaoliang Wu ◽  
Guoqiang Wan ◽  
Rongjie Wang ◽  
...  
Keyword(s):  
Markov Model ◽  
Copy Number ◽  
Hidden Markov ◽  
Copy Number Variant ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Variant Detection ◽  
Copy Number Variant Detection

scholarly journals Evaluation of somatic copy number estimation tools for whole-exome sequencing data

2015 ◽  
Vol 17 (2) ◽  
pp. 185-192 ◽  
Author(s):  
Jae-Yong Nam ◽  
Nayoung K. D. Kim ◽  
Sang Cheol Kim ◽  
Je-Gun Joung ◽  
Ruibin Xi ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Sequencing Data ◽  
Copy Number Estimation ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

scholarly journals SECNVs: A Simulator of Copy Number Variants and Whole-Exome Sequences from Reference Genomes

2019 ◽  
Author(s):  
Yue Xing ◽  
Alan R. Dabney ◽  
Xiao Li ◽  
Guosong Wang ◽  
Clare A. Gill ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Software Applications ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

AbstractCopy number variants are insertions and deletions of 1 kb or larger in a genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested SECNVs (Simulator of Exome Copy Number Variants), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.

scholarly journals Improving Copy Number Variant Detection from Sequencing Data with a Combination of Programs and a Predictive Model

2020 ◽  
Vol 22 (1) ◽  
pp. 40-49 ◽  
Author(s):  
Salla Välipakka ◽  
Marco Savarese ◽  
Lydia Sagath ◽  
Meharji Arumilli ◽  
Teresa Giugliano ◽  
...  
Keyword(s):  
Predictive Model ◽  
Copy Number ◽  
Copy Number Variant ◽  
Sequencing Data ◽  
Variant Detection ◽  
Copy Number Variant Detection

scholarly journals DeAnnCNV: a tool for online detection and annotation of copy number variations from whole-exome sequencing data

2015 ◽  
Vol 43 (W1) ◽  
pp. W289-W294 ◽  
Author(s):  
Yuanwei Zhang ◽  
Zhenhua Yu ◽  
Rongjun Ban ◽  
Huan Zhang ◽  
Furhan Iqbal ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Variations ◽  
Online Detection ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

scholarly journals CEQer: A Graphical Tool for Copy Number and Allelic Imbalance Detection from Whole-Exome Sequencing Data

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e74825 ◽  
Author(s):  
Rocco Piazza ◽  
Vera Magistroni ◽  
Alessandra Pirola ◽  
Sara Redaelli ◽  
Roberta Spinelli ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Allelic Imbalance ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Graphical Tool ◽  
Whole Exome Sequencing Data

scholarly journals GSTM1 copy number is not associated with risk of kidney failure in a large cohort

2019 ◽  
Author(s):  
Yanfei Zhang ◽  
Waleed Zafar ◽  
Dustin N. Hartzel ◽  
Marc S. Williams ◽  
Adrienne Tin ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Exome Sequencing ◽  
Kidney Failure ◽  
Copy Number ◽  
Large Cohort ◽  
Health Record ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

AbstractDeletion of glutathione S-transferase µ1 (GSTM1) is common in populations and has been asserted to associate with chronic kidney disease progression in some research studies. The association needs to be validated. We estimated GSTM1 copy number using whole exome sequencing data in the DiscovEHR cohort. Kidney failure was defined as requiring dialysis or receiving kidney transplant using data from the electronic health record and linkage to the United States Renal Data System, or the most recent eGFR < 15 ml/min/1.73m2. In a cohort of 46,983 unrelated participants, 28.8% of blacks and 52.1% of whites had 0 copies of GSTM1. Over a mean of 9.2 years follow-up, 645 kidney failure events were observed in 46,187 white participants, and 28 in 796 black participants. No significant association was observed between GSTM1 copy number and kidney failure in Cox regression adjusting for age, sex, BMI, smoking status, genetic principal components, or co-morbid conditions (hypertension, diabetes, heart failure, coronary artery disease, and stroke), whether using a genotypic, dominant, or recessive model. In sensitivity analyses, GSTM1 copy number was not associated with kidney failure in participants that were 45 years or older at baseline, had baseline eGFR < 60 ml/min per 1.73 m2, or with baseline year between 1996-2002. In conclusion, we found no association between GSTM1 copy number and kidney failure in a large cohort study.Translational StatementDeletion of GSTM1 has been shown to be associated with higher risk of kidney failure. However, inconsistent results have been reported. We used electronic health record and whole exome sequencing data of a large cohort from a single healthcare system to evaluate the association between GSTM1 copy number and risk of kidney failure. We found no significant association between GSTM1 copy number and risk of kidney failure overall, or in multiple sensitivity and subgroup analyses.

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