tadar: an R/Bioconductor package to reduce eQTL noise in differential expression analysis
Guardado en:
| 發表在: | bioRxiv (Feb 13, 2025) |
|---|---|
| 主要作者: | |
| 其他作者: | , |
| 出版: |
Cold Spring Harbor Laboratory Press
|
| 主題: | |
| 在線閱讀: | Citation/Abstract Full Text - PDF Full text outside of ProQuest |
| 標簽: |
沒有標簽, 成為第一個標記此記錄!
|
| Resumen: | Despite the relative maturity of bulk RNA-sequencing, compared to more recent developments such as single-cell and spatial RNA-sequencing, biases which impact data analysis continue to surface. One such bias, termed "Differential Allelic Representation" (DAR), is particularly evident when experimental samples are taken from non-isogenic genetic backgrounds. DAR is an uneven distribution of polymorphic loci between groups of experimental samples undergoing differential gene expression (DGE) analysis. When unequally represented polymorphic loci are also expression quantitative trait loci (eQTLs), DAR can lead to differences in gene expression which are not directly relevant to the primary research objectives. To mitigate DAR in both new and existing datsets, we introduce tadar, a Bioconductor package designed to facilitate transcriptome analysis by accounting for differential allelic representation. tadar implements a methodology that calculates a DAR metric at each polymorphic locus across the genome, which then serves as a predictive measure of a locus' potential to cause eQTL-driven expression differences. This metric is then used to reduce eQTL noise in bulk RNA-Sequencing data.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://doi.org/10.5281/zenodo.14769085 |
|---|---|
| ISSN: | 2692-8205 |
| DOI: | 10.1101/2025.02.11.637777 |
| Fuente: | Biological Science Database |