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MDEHT: a multivariate approach for detecting differential expression of microRNA isoform data in RNA-sequencing studies. Bioinformatics 2020 05 01;36(9):2657-2664

Date

01/14/2020

Pubmed ID

31930386

Pubmed Central ID

PMC7203753

DOI

10.1093/bioinformatics/btaa015

Scopus ID

2-s2.0-85084380046   2 Citations

Abstract

MOTIVATION: miRNA isoforms (isomiRs) are produced from the same arm as the archetype miRNA with a few nucleotides different at 5 and/or 3 termini. These well-conserved isomiRs are functionally important and have contributed to the evolution of miRNA genes. Accurate detection of differential expression of miRNAs can bring new insights into the cellular function of miRNA and a further improvement in miRNA-based diagnostic and prognostic applications. However, very few methods take isomiR variations into account in the analysis of miRNA differential expression.

RESULTS: To overcome this challenge, we developed a novel approach to take advantage of the multidimensional structure of isomiR data from the same miRNAs, termed as a multivariate differential expression by Hotelling's T2 test (MDEHT). The utilization of the information hidden in isomiRs enables MDEHT to increase the power of identifying differentially expressed miRNAs that are not marginally detectable in univariate testing methods. We conducted rigorous and unbiased comparisons of MDEHT with seven commonly used tools in simulated and real datasets from The Cancer Genome Atlas. Our comprehensive evaluations demonstrated that the MDEHT method was robust among various datasets and outperformed other commonly used tools in terms of Type I error rate, true positive rate and reproducibility.

AVAILABILITY AND IMPLEMENTATION: The source code for identifying and quantifying isomiRs and performing miRNA differential expression analysis is available at https://github.com/amanzju/MDEHT.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Author List

Amanullah M, Yu M, Sun X, Luo A, Zhou Q, Zhou L, Hou L, Wang W, Lu W, Liu P, Lu Y

Author

Pengyuan Liu PhD Adjunct Professor in the Physiology department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Base Sequence
Gene Expression Profiling
MicroRNAs
Protein Isoforms
Reproducibility of Results
Sequence Analysis, RNA