Artikel: Robust identification of regulatory variants (eQTLs) using a differential expression framework developed for RNA-sequencing.
Journal of animal science and biotechnology
2023 Band 14, Heft 1, Seite(n) 62
Abstract: Background: A gap currently exists between genetic variants and the underlying cell and tissue biology of a trait, and expression quantitative trait loci (eQTL) studies provide important information to help close that gap. However, two concerns that ... ...
Abstract | Background: A gap currently exists between genetic variants and the underlying cell and tissue biology of a trait, and expression quantitative trait loci (eQTL) studies provide important information to help close that gap. However, two concerns that arise with eQTL analyses using RNA-sequencing data are normalization of data across samples and the data not following a normal distribution. Multiple pipelines have been suggested to address this. For instance, the most recent analysis of the human and farm Genotype-Tissue Expression (GTEx) project proposes using trimmed means of M-values (TMM) to normalize the data followed by an inverse normal transformation. Results: In this study, we reasoned that eQTL analysis could be carried out using the same framework used for differential gene expression (DGE), which uses a negative binomial model, a statistical test feasible for count data. Using the GTEx framework, we identified 35 significant eQTLs (P < 5 × 10 Conclusions: Our results show that transforming RNA-sequencing data to fit a normal distribution prior to eQTL analysis is not required when the DGE framework is employed. Our proposed approach detected biologically relevant variants that otherwise would not have been identified due to data transformation to fit a normal distribution. |
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Sprache | Englisch |
Erscheinungsdatum | 2023-05-05 |
Erscheinungsland | England |
Dokumenttyp | Journal Article |
ZDB-ID | 2630162-3 |
ISSN | 2049-1891 ; 1674-9782 |
ISSN (online) | 2049-1891 |
ISSN | 1674-9782 |
DOI | 10.1186/s40104-023-00861-0 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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