Whole-Genome Shotgun Sequence CNV Detection Using Read Depth View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-07-24

AUTHORS

Fatma Kahveci , Can Alkan

ABSTRACT

With the developments in high-throughput sequencing (HTS) technologies, researchers have gained a powerful tool to identify structural variants (SVs) in genomes with substantially less cost than before. SVs can be broadly classified into two main categories: balanced rearrangements and copy number variations (CNVs). Many algorithms have been developed to characterize CNVs using HTS data, with focus on different types and size range of variants using different read signatures. Read depth (RD) based tools are more common in characterizing large (>10 kb) CNVs since RD strategy does not rely on the fragment size and read length, which are limiting factors in read pair and split read analysis. Here we provide a guideline for a user friendly tool for detecting large segmental duplications and deletions that can also predict integer copy numbers for duplicated genes. More... »

PAGES

61-72

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4939-8666-8_4

DOI

http://dx.doi.org/10.1007/978-1-4939-8666-8_4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105777655

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30039363


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