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Using XCAVATOR and EXCAVATOR2 to Identify CNVs from WGS, WES, and TS Data

Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation but also associated with many disease states. In recent years, the identification of CNVs from high-throughput sequencing experi- ments has become a common practice for both research and clinical purposes. Several computational methods have been developed so far. In this unit, we describe and give instructions on how to run two read count–based tools, XCAVATOR and EXCAVATOR2, which are tailored for the detection of both germline and somatic CNVs from different sequencing experiments (whole- genome, whole-exome, and targeted) in various disease contexts and population genetic studies.

2018

External authors: Roberto Semeraro (UniFi), Alberto Magi (UniFi)
IIT authors:

Type: Capitolo di libro
Field of reference: Computer Science & Engineering

File: D'Aurizio_et_al-2018-Current_Protocols_in_Human_Genetics.pdf

Activity: Computational Biology