miR-MaGiC improves quantification accuracy for small RNA-seq

BMC Research Notes
Pamela H RussellKaterina Kechris

Abstract

Many tools have been developed to profile microRNA (miRNA) expression from small RNA-seq data. These tools must contend with several issues: the small size of miRNAs, the small number of unique miRNAs, the fact that similar miRNAs can be transcribed from multiple loci, and the presence of miRNA isoforms known as isomiRs. Methods failing to address these issues can return misleading information. We propose a novel quantification method designed to address these concerns. We present miR-MaGiC, a novel miRNA quantification method, implemented as a cross-platform tool in Java. miR-MaGiC performs stringent mapping to a core region of each miRNA and defines a meaningful set of target miRNA sequences by collapsing the miRNA space to "functional groups". We hypothesize that these two features, mapping stringency and collapsing, provide more optimal quantification to a more meaningful unit (i.e., miRNA family). We test miR-MaGiC and several published methods on 210 small RNA-seq libraries, evaluating each method's ability to accurately reflect global miRNA expression profiles. We define accuracy as total counts close to the total number of input reads originating from miRNAs. We find that miR-MaGiC, which incorporates both stringency an...Continue Reading

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Citations

Nov 15, 2019·BMC Genomics·Gordon KordasKaterina Kechris
Dec 15, 2020·Briefings in Bioinformatics·Georges Pierre SchmartzAndreas Keller

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Methods Mentioned

BETA
RNA-seq

Software Mentioned

miRanalyzer
miR
Chimira
miRSeq
iSRAP
script
MaGiC
MIMAT
Bowtie
mirTools

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