A novel copy number variation detection array for the diagnostics of neuromuscular disorders

2017 ◽  
Vol 27 ◽  
pp. S182
Author(s):  
L. Sagath ◽  
V. Lehtokari ◽  
C. Wallgren-Pettersson ◽  
K. Pelin ◽  
K. Kiiski
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Neuromuscular Disorders ◽  
Number Variation ◽  
Copy Number Variation Detection

scholarly journals An Extended Targeted Copy Number Variation Detection Array Including 187 Genes for the Diagnostics of Neuromuscular Disorders

2018 ◽  
Vol 5 (3) ◽  
pp. 307-314 ◽  
Author(s):  
Lydia Sagath ◽  
Vilma-Lotta Lehtokari ◽  
Salla Välipakka ◽  
Bjarne Udd ◽  
Carina Wallgren-Pettersson ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Neuromuscular Disorders ◽  
Number Variation ◽  
Copy Number Variation Detection

scholarly journals CNV-BAC: Copy number Variation Detection in Bacterial Circular Genome

2020 ◽  
Vol 36 (12) ◽  
pp. 3890-3891
Author(s):  
Linjie Wu ◽  
Han Wang ◽  
Yuchao Xia ◽  
Ruibin Xi
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Genome Structure ◽  
Real Data ◽  
Read Depth ◽  
Supplementary Information ◽  
Circular Genome ◽  
Number Variation ◽  
Copy Number Variation Detection ◽  
Cnv Detection

Abstract Motivation Whole-genome sequencing (WGS) is widely used for copy number variation (CNV) detection. However, for most bacteria, their circular genome structure and high replication rate make reads more enriched near the replication origin. CNV detection based on read depth could be seriously influenced by such replication bias. Results We show that the replication bias is widespread using ∼200 bacterial WGS data. We develop CNV-BAC (CNV-Bacteria) that can properly normalize the replication bias and other known biases in bacterial WGS data and can accurately detect CNVs. Simulation and real data analysis show that CNV-BAC achieves the best performance in CNV detection compared with available algorithms. Availability and implementation CNV-BAC is available at https://github.com/XiDsLab/CNV-BAC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals 28: Copy Number Variation Detection Using Next-Generation Sequencing

2015 ◽  
Vol 143 (suppl_1) ◽  
pp. A013-A013
Author(s):  
Linda B. Baughn ◽  
Getiria Onsongo ◽  
Matthew Bower ◽  
Christine Henzler ◽  
Kevin A.T. Silverstein ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Copy Number Variation ◽  
Copy Number ◽  
Next Generation ◽  
Number Variation ◽  
Copy Number Variation Detection ◽  
Generation Sequencing

scholarly journals Single-cell copy number variation detection

2011 ◽  
Vol 12 (8) ◽  
pp. R80 ◽  
Author(s):  
Jiqiu Cheng ◽  
Evelyne Vanneste ◽  
Peter Konings ◽  
Thierry Voet ◽  
Joris R Vermeesch ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Single Cell ◽  
Copy Number ◽  
Number Variation ◽  
Copy Number Variation Detection
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