A statistical approach for identifying primary substrates of ZSWIM8-mediated microRNA degradation in small-RNA sequencing data
Name
12859_2023_Article_5306.pdf
Size
1.89 MB
Format
Adobe PDF
Checksum (MD5)
fa1bd15aab68a2ab3abe2c54191875d6
Author(s) •
Wang, Peter Y.
Bartel, David P.
Date Issued
May 12, 2023
Publisher
BioMed Central
Citation
BMC Bioinformatics. 2023 May 12;24(1):195
Version
Final published version
Abstract
Abstract
Background
One strategy for identifying targets of a regulatory factor is to perturb the factor and use high-throughput RNA sequencing to examine the consequences. However, distinguishing direct targets from secondary effects and experimental noise can be challenging when confounding signal is present in the background at varying levels.
Results
Here, we present a statistical modeling strategy to identify microRNAs that are primary substrates of target-directed miRNA degradation (TDMD) mediated by ZSWIM8. This method uses a bi-beta-uniform mixture (BBUM) model to separate primary from background signal components, leveraging the expectation that primary signal is restricted to upregulation and not downregulation upon loss of ZSWIM8. The BBUM model strategy retained the apparent sensitivity and specificity of the previous ad hoc approach but was more robust against outliers, achieved a more consistent stringency, and could be performed using a single cutoff of false discovery rate (FDR).
Conclusions
We developed the BBUM model, a robust statistical modeling strategy to account for background secondary signal in differential expression data. It performed well for identifying primary substrates of TDMD and should be useful for other applications in which the primary regulatory targets are only upregulated or only downregulated. The BBUM model, FDR-correction algorithm, and significance-testing methods are available as an R package at
https://github.com/wyppeter/bbum
.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Howard Hughes Medical Institute
Whitehead Institute for Biomedical Research
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1186/s12859-023-05306-z