| Autor: |
Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Julian Matschinske, Tobias Frisch, Markus List, Julian Späth, Stefan Weiss, Uwe Völker, Esa Pitkänen, Dominik Heider, Nina Kerstin Wenke, Georgios Kaissis, Daniel Rueckert, Tim Kacprowski, Jan Baumbach |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Genome Biology, Vol 23, Iss 1, Pp 1-24 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1474-760X |
| DOI: |
10.1186/s13059-021-02562-1 |
| Popis: |
Abstract Meta-analysis has been established as an effective approach to combining summary statistics of several genome-wide association studies (GWAS). However, the accuracy of meta-analysis can be attenuated in the presence of cross-study heterogeneity. We present sPLINK, a hybrid federated and user-friendly tool, which performs privacy-aware GWAS on distributed datasets while preserving the accuracy of the results. sPLINK is robust against heterogeneous distributions of data across cohorts while meta-analysis considerably loses accuracy in such scenarios. sPLINK achieves practical runtime and acceptable network usage for chi-square and linear/logistic regression tests. sPLINK is available at https://exbio.wzw.tum.de/splink . |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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