Characterization of somatically-acquired copy number alterations in chronic lymphocytic leukaemia using shallow whole genome sequencing
Characterization of somatically-acquired copy number alterations in chronic lymphocytic leukaemia using shallow whole genome sequencing
Shallow whole genome sequencing (sWGS) is a simple, robust, and cost-effective technique recently optimized for the identification of copy number aberrations (CNAs) in tumor samples. This multiplexed methodology sequences 50 bp from one end of the DNA molecule, generating ˜0.1× coverage, and utilizes the observed sequence depth across the genome to infer copy number. It is amenable to low quantities of input DNA, sequencing costs are modest, processing is compatible with low-output instruments, and downstream analysis is simplified by the use of freely available bioinformatics tools and a data analysis package written especially for the analysis of sWGS data. It is the aim of this chapter to introduce the fundamental concepts of sWGS and to provide an overview of the steps involved in a successful sWGS experiment.
327-353
Strefford, Jonathan
3782b392-f080-42bf-bdca-8aa5d6ca532f
Parker, Helen
33e0cd81-d45f-49bc-9539-09345d79d895
Bryant, Dean
10ed83e8-8080-4d9c-bba5-df9d4eec3a10
2019
Strefford, Jonathan
3782b392-f080-42bf-bdca-8aa5d6ca532f
Parker, Helen
33e0cd81-d45f-49bc-9539-09345d79d895
Bryant, Dean
10ed83e8-8080-4d9c-bba5-df9d4eec3a10
Strefford, Jonathan, Parker, Helen and Bryant, Dean
(2019)
Characterization of somatically-acquired copy number alterations in chronic lymphocytic leukaemia using shallow whole genome sequencing.
In,
Malek, Sami
(ed.)
Chronic Lymphocytic Leukemia.
(Methods in Molecular Biology, 1881)
New York, NY.
Humana Press, .
(doi:10.1007/978-1-4939-8876-1_23).
Record type:
Book Section
Abstract
Shallow whole genome sequencing (sWGS) is a simple, robust, and cost-effective technique recently optimized for the identification of copy number aberrations (CNAs) in tumor samples. This multiplexed methodology sequences 50 bp from one end of the DNA molecule, generating ˜0.1× coverage, and utilizes the observed sequence depth across the genome to infer copy number. It is amenable to low quantities of input DNA, sequencing costs are modest, processing is compatible with low-output instruments, and downstream analysis is simplified by the use of freely available bioinformatics tools and a data analysis package written especially for the analysis of sWGS data. It is the aim of this chapter to introduce the fundamental concepts of sWGS and to provide an overview of the steps involved in a successful sWGS experiment.
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e-pub ahead of print date: 23 October 2018
Published date: 2019
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Local EPrints ID: 425835
URI: http://eprints.soton.ac.uk/id/eprint/425835
PURE UUID: 159c4034-8dc1-4bdf-8702-97210c1042b3
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Date deposited: 05 Nov 2018 17:30
Last modified: 16 Mar 2024 04:19
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Author:
Dean Bryant
Editor:
Sami Malek
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