dc.contributor.author |
Emde, Anne-Katrin |
|
dc.contributor.author |
Phipps-Green, Amanda |
|
dc.contributor.author |
Cadzow, Murray |
|
dc.contributor.author |
Gallagher, C Scott |
|
dc.contributor.author |
Major, Tanya J |
|
dc.contributor.author |
Merriman, Marilyn E |
|
dc.contributor.author |
Topless, Ruth K |
|
dc.contributor.author |
Takei, Riku |
|
dc.contributor.author |
Dalbeth, Nicola |
|
dc.contributor.author |
Murphy, Rinki |
|
dc.contributor.author |
Stamp, Lisa K |
|
dc.contributor.author |
de Zoysa, Janak |
|
dc.contributor.author |
Wilcox, Philip L |
|
dc.contributor.author |
Fox, Keolu |
|
dc.contributor.author |
Wasik, Kaja A |
|
dc.contributor.author |
Merriman, Tony R |
|
dc.contributor.author |
Castel, Stephane E |
|
dc.coverage.spatial |
England |
|
dc.date.accessioned |
2021-12-20T03:35:21Z |
|
dc.date.available |
2021-12-20T03:35:21Z |
|
dc.date.issued |
2021-11-1 |
|
dc.identifier.citation |
BMC genomics 22(1):666 Nov 2021 |
|
dc.identifier.issn |
1471-2164 |
|
dc.identifier.uri |
https://hdl.handle.net/2292/57842 |
|
dc.description.abstract |
BACKGROUND: Historically, geneticists have relied on genotyping arrays and imputation to study human genetic variation. However, an underrepresentation of diverse populations has resulted in arrays that poorly capture global genetic variation, and a lack of reference panels. This has contributed to deepening global health disparities. Whole genome sequencing (WGS) better captures genetic variation but remains prohibitively expensive. Thus, we explored WGS at "mid-pass" 1-7x coverage. RESULTS: Here, we developed and benchmarked methods for mid-pass sequencing. When applied to a population without an existing genomic reference panel, 4x mid-pass performed consistently well across ethnicities, with high recall (98%) and precision (97.5%). CONCLUSION: Compared to array data imputed into 1000 Genomes, mid-pass performed better across all metrics and identified novel population-specific variants with potential disease relevance. We hope our work will reduce financial barriers for geneticists from underrepresented populations to characterize their genomes prior to biomedical genetic applications. |
|
dc.language |
eng |
|
dc.publisher |
Springer Science and Business Media LLC |
|
dc.relation.ispartofseries |
BMC Genomics |
|
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
|
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
|
dc.rights.uri |
https://creativecommons.org/licenses/by/4.0/ |
|
dc.rights.uri |
https://www.biomedcentral.com/about/open-access |
|
dc.subject |
Genome |
|
dc.subject |
Genome, Human |
|
dc.subject |
Genome-Wide Association Study |
|
dc.subject |
Genomics |
|
dc.subject |
Genotype |
|
dc.subject |
Humans |
|
dc.subject |
Polymorphism, Single Nucleotide |
|
dc.subject |
Whole Genome Sequencing |
|
dc.subject |
06 Biological Sciences |
|
dc.subject |
08 Information and Computing Sciences |
|
dc.subject |
11 Medical and Health Sciences |
|
dc.title |
Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations. |
|
dc.type |
Journal Article |
|
dc.identifier.doi |
10.1186/s12864-021-07949-9 |
|
pubs.issue |
1 |
|
pubs.begin-page |
666 |
|
pubs.volume |
22 |
|
dc.date.updated |
2021-11-09T01:36:05Z |
|
dc.rights.holder |
Copyright: The author |
en |
pubs.author-url |
https://www.ncbi.nlm.nih.gov/pubmed/34719381 |
|
pubs.publication-status |
Published online |
|
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
Journal Article |
|
pubs.elements-id |
872899 |
|
dc.identifier.eissn |
1471-2164 |
|
dc.identifier.pii |
10.1186/s12864-021-07949-9 |
|
pubs.number |
666 |
|
pubs.online-publication-date |
2021-11-1 |
|