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Updated: Jun 18, 2025

mirMachine: A One-Stop Shop for Plant miRNA Annotation
Published on: May 1, 2021
miRglmm: a generalized linear mixed model of isomiR-level counts improves estimation of miRNA-level differential
Andrea M Baran1, Arun H Patil2, Ernesto Aparicio-Puerta1
1Department of Biostatistics and Computational Biology, University of Rochester Medical Center, 265 Crittenden Blvd., Box 630, Rochester, NY 14642, USA.
Abstract:
MicroRNA-seq data is produced by aligning small RNA sequencing reads of different miRNA transcript isoforms, called isomiRs, to known microRNAs. Aggregation to microRNA-level counts discards information and violates core assumptions of differential expression (DE) methods developed for mRNA-seq data. We establish miRglmm, a DE method for microRNA-seq data, that uses a generalized linear mixed model of isomiR-level counts, facilitating detection of miRNA with differential expression or differential isomiR usage. We demonstrate that miRglmm outperforms current DE methods in estimating DE for miRNA, whether or not there is significant isomiR variability, and simultaneously provides estimates of isomiR-level DE.

