G-CNV: A GPU-based Tool for Preparing Data to Detect CNVs with Read Depth Methods

G-CNV: A GPU-based Tool for Preparing Data to Detect CNVs with Read Depth Methods

Copy Number Variations (CNVs) are the most prevalent types of structural variations (SVs) in the human genome and are involved in a wide range of common human diseases. Different computational methods have been devised to detect this type of SVs and to study how they are implicated in human diseases...

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Bibliographic Details
Main Authors: Andrea eManconi, Emanuele eManca, Alessandro eOrro, Giuliano eArmano, Matteo eGnocchi, Marco eMoscatelli, Luciano eMilanesi
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-03-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
CNV
Parallel Computing
HTS
GPUs
read depth
Online Access:http://journal.frontiersin.org/Journal/10.3389/fbioe.2015.00028/full

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