| Title: |
OTTERS:a powerful TWAS framework leveraging summary-level reference data |
| Authors: |
Dai,Qile; Zhou,Geyu; Võsa,Urmo; Franke,Lude; Battle,Alexis; Teumer,Alexander; Lehtimäki,Terho; Raitakari,Olli T.; Esko,Tõnu; Deelen, Patrick; eQTLGen Consortium; Genetica; Genetica Klinische Genetica; Brain; Genetic Risks; Neurologen |
| Publication Year: |
2023 |
| Subject Terms: |
General Chemistry; General Biochemistry,Genetics and Molecular Biology; General Physics and Astronomy |
| Description: |
Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies. |
| Document Type: |
article in journal/newspaper |
| File Description: |
text/plain |
| Language: |
English |
| ISSN: |
2041-1723 |
| Relation: |
https://dspace.library.uu.nl/handle/1874/458743 |
| Availability: |
https://dspace.library.uu.nl/handle/1874/458743 |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.CC3749C6 |
| Database: |
BASE |