List of tools updated 01.01.2021 (Cite: Glogovitis, I.; Yahubyan, G.; Würdinger, T.; Koppers-Lalic, D.; Baev, V. isomiRs–Hidden Soldiers in the miRNA Regulatory Army, and How to Find Them? Biomolecules 2021, 11, 41. https://doi.org/10.3390/biom11010041
| Tool name | Type | Tool Features | Year | Authors | Journal URL Reference (DOI number) |
|---|---|---|---|---|---|
| miRMaster | Web | ● Quantification of miRNAs and non-coding RNAs ● Discovering of new miRNAs and isomiRs ● Discovering of new miRNAs and isomiRs ● Quantification on known and novel miRNA with miRDeep2 ● Preprocessing (adapter trimming, quality filtering, read collapsing) ● Mapping with Bowtie to various ncRNA (rRNAs, snRNAs, snoRNAs, scaRNAs, lincRNAs, piRNAs, tRNAs) ● Exogenous miRNAs mapping with bacteria and viruses ● Used for validation used samples from lung and blood samples from PAX blood RNA pool |
2017 | Tobias Fehlmann et all. | Nucleic Acids Research Open Access [URL] 10.1093/nar/ gkx595 |
| QuickMIRSeq | Linux | ● Quantify miRNAs and isomiRs ● Avoid of multiple mapping issue of reads of identical sequences ● Clustering and grouping of identical and similar sequences ● Trimming adapters, collapsing, joint mapping with Bowtie ● Remapping reads with mismatches to a reference genome to further reduce the number of false hits |
2017 | Shanrong Zhao et all. | BMC Bioinformatics Open Access [URL] 10.1186/s12859 -017-1601-4 |
| iMir | Linux Mac |
● Identification of miRNAs and other sncRNAs, such as piRNAs ● Adapter trimming, quality filtering, differential expression analysis ● Analysis of sncRNAs and novel miRNAs ● Identification of isomirs using miRanalyzer ● Using miRAnalyzer and miRDeep2 ● Statistical analysis to remove low expressed sncRNAs ● Differential Expression using Deseq Quantile normalization ● Target Prediction using TargetScan and miRanda |
2013 | Giorgio Giurato et all. | BMC Bioinformatics Open access [URL] 10.1186/1471 -2105-14-362 |
| MIR-isomiRExp | Web | ● Analyze the expression patterns or miRNA/isomer levels ● miRNA maturation and processing mechanism at isomiRs levels ● Using MirBase DB, mapping with Bowtie ● Differential expression using Deseq ● Analysis at the isomiR levels based/independent on miRNA locus ● Arm-switching analysis |
2016 | Li Guo et all. | Nature Open Access [URL] 10.1038/ srep23700 |
| miRNAgFree | Linux Windows |
● miRNA prediction based on biogenesis features (known 5’ homogeneity) and isomiR duplex forming ● Uses the sRNAbench preprocessing |
2017 | EL Aparicio et all. | BioRxiv [URL] 10.1101/193094 |
| isomiRID | Linux Mac |
● Identification of 5’, 3’ and polymorphic isomiRs ● Identification of non-templated 5’ or 3’ end and variations ● It could be applied to every organism (plants + animals) ● Detection of isomiRs with one mismatch ● Mapping in pre-miRNAs with Bowtie |
2013 | Luiz Felipe Valter de Oliveira et all. | Bioinformatics [URL] 10.1093/ bioinformatics/ btt424 |
| MIRPIPE | Web | ● Rapid and simple browser-based miRNA homology detection and quantification of miRNAs ● Read counts from isomiRs of the same miRNA are combined. ● Using FASTX-tollkit, Cutadapt, BLASTN |
2014 | Carsten Kuenne et all. | Bioinformatics [URL] 10.1093/ bioinformatics/ btu573 |
| CASMIR | Standalone Linux |
● Sequence-oriented isomiR annotation which allows unbiased identification of global isomiRs from small sequencing data ● Alignment against canonical and precursors from miRBase ● Discovering of canonical, 5’, 3’, polymorphic, mixed type, non-templated isomiRs, quantification using miRDeep2 ● In-house trimming and size filtering ● BLAST with in house custom isomiR-BLAST alignment tool ● Differential expression performed with a Poisson regression model combined with a quasi-likelihood approach and AUC based on methods of DeLong and Clarke-Pearson |
2018 | Chung Wah Wu et all. | BMC Genomics Open Access [URL] 10.1186/s1286 4-018-4794-7 |
| IsomiR-SEA | Linux Windows Mac |
● Provide users with a complete and accurate picture of the miRNAs, isomiRs and conserved miRNA:mRNA interaction sites ● Provide accurate miRNA and isomiRs expression levels ● Use a specialized algorithm for alignment ● Evaluates the positions of the encountered mismatches in analyzed tags |
2016 | Gianvito Urgese et all. | BMC Bioinformatics [URL] 10.1186/s12859 -016-0958-0 |
| DeAnnIso | Web | ● Detection and Annotation of IsomiRs from sRNA se- quencing data ● Еxtract the differentially expressing isomiRs with isomiRs expression, isomiRs classification from paired or multiple samples ● Tissue specific isomiR expression ● Using Bowtie and BLAST with miRBase ● Normalization with RPM ● isomiRs’ classification, 5’ isomiRs, 3’ isomiRs, isomiRs with internal modifications, templated and non-templated ● Target analysis and enrichment analysis of isomiRs with miRanda or RNA hybrid |
2016 | Yuanwei Zhang et all. | Nucleic Acids Research [URL] 10.1093/nar/ gkw427 |
| IsomiRage | Windows Mac |
● Identification of miRNA variants (canonical miRNAs, templated and non-templated isomiRs) ● Detects and groups all 3’-,5’- and trimmed variants ● Uses reference sequences from miRBase ● Classification of isomiRs according to the type of modification (uridylation, adenylation,etc) ● Mapping performed with Bowtie with no mismatches to reference and custom genome ● Normalization with RPM and read counts that can be used for comparisons of fold changes and other downstream analyses |
2014 | Muller Heiko et all. | Frontiers in Bioengineering and Biotechnology [URL] 10.3389/fbioe. 2014.00038 |
| QuagmiR | Standalone Web |
● Designed for the detection and annotation of heterogeneous isomiRs ● Provide extensive customization of the process and reference databases according to user’s diverse research needs ● Can be used to analyze both private datasets and the public datasets that are available to authorized researchers through the CGC |
2018 | Xavier Bofill-De Ros et all. | Bioimformatics [URL] 10.1093/ bioinformatics/ bty843 |
| Jasmine | R + Java | ● Identification of isomiR populations. ● Propose a comprehensive isomiR nomenclature ● Uses curated miRBase annotation. ● Adapter trimming (trimmomatic, cutadapt) ● Collapsing trimmed reads (fastx_collapser, fastq _to_fasta from FASTX-toolkit), Quality control (FastQC) ● Mapping with Bowtie with at least one mismatch ● Uses miRBase database |
2019 | Xiangfu Zhong et all. | Bioinformatics [URL] 10.1093/ bioinformatics/ btz806 |
| CBS-miRSeq | Linux Docker VM |
● Color-spaced raw reads ● Read length distribution, summary of adapter removal, mapping statistics, and raw expression count matrix of known miRNAs. ● Using Bowtie with reference genome ● Differential expression analysis using Deseq2, EdgeR ● Identifies isomiRs using miRspring ● Predicts novel miRNA candidates using miRDeep2 ● Predicts the most consistent miRNA:mRNA unique pairs, using RNAhybrid, miRanda |
2019 | Rupesh K. Kesharwani et all. | Computers in Biology and Medicine [URL] 10.1016/ j.compbiomed. 2019.05.019. |
| sRNAtoolbox | Web | ●Expression profiling of small RNAs, prediction of novel microRNAs, analysis of isomiRs ● Differential expression using DESeq, edgeR, and NOISeq ● Target prediction onuser-provided input data based on Miranda, PITA and TargetSpy ● Visualization of sRNA expression data in a genome context using jBrowse |
2015 | Antonio Rueda et all. | Nucleic Acids Research [URL] 10.1093/nar/ gkv555 |
| sRNAnalyzer | Web | ● miRNA profiling strategies for isomiRs ● Detection of potential SNPs in miRNAs ● Uses Cutadapt, Printseq, FastX for preprocessing and Bowtie for mapping; MirBase and MirGen DB ● Use of LPM (local probability mapping) strategy to increase mapping specificity ● Extensive rRNA and tRNA filtering steps to enhance the accuracy of exogenous RNA mapping ● Exogenous RNA mapping process using sRNAnalyzer |
2017 | Xiaogang Wu et all. | Nucleic Acids Research Open Access [URL] 10.1093/nar/ gkx999 |
| mirPRo | Linux | ● Quantify known miRNAs ● Predict novel miRNAs and miRNA family expression quantification ● IsomiRs identification and categorization ● Arm switching detection ● Using Novoalign, HTSeq and pre-miRNAs from miRBase ● Using DESeq to perform differential expression profile analysis for known and novel mature miRNAs |
2015 | Jieming Shi et all. | Nature Open Access [URL] 10.1038/ srep14617 |
| miRge | Standalone | ● MirGeneDB miRNAs were used to assemble positive clusters (known miRNAs and tRNA, snoRNA, rRNA or mRNA were used to assemble negative clusters (known non-miRNAs) ● Identification of isomiRs ● Novel miRNA detection ● Preprocessing with Cutadapt and mapping (Bowtie) ● Using miRbase and miRGen DB ● Detection of A-to-I editing |
2015 | Alexander S. Baras et all. | Plos one Open Access [URL] 10.1371/journal. pone.0143066 |
| miRDis | Web | ● Systematic annotation of known miRNAs and other noncoding RNAs based on read mapped regions ● Prediction of novel miRNAs and noncoding RNAs through assigning ambiguous reads to unique genome region with well-predicted RNA structure ● Detection of candidate exogenous miRNAs transported from dietary species ● Using FASTQC, Cutadapt, Bowtie and EdgeR |
2017 | Hanyuan Zhang et all. | Briefings in Bioinformatics Open Access [URL] 10.1093/bib/ bbw140 |
| miRMOD | Windows | ● Identifies and analyzes miRNA 3’ and 5’ modifications (non-templated additions as well as trimming) ● Using Bowtie with reference genome/pre-miRNA ● Provides useful statistics about various types of miRNA modifications along with its frequencies. ● Target alteration analysis |
2015 | Abhinav Kaushik et all. | PeerJ Open Access [URL] 10.7717/ peerj.1332 |
| mirTools 2.0 | Web | ● Detection of various types of ncRNAs (miRNA, tRNA, snRNA, snoRNA, rRNA and piRNA) ● Identify miRNA-targeted genes ● Performs functional annotation or miRNA targets (GO, KEGG, PPI) ● Detect differentially expressed ncRNAs with RPM and the Bayesian method ● Detect novel miRNAs using miRDeep |
2013 | Jinyu Wu et all. | RNA Biology [URL] 10.4161/ rna.25193 |
| Chimira | Web | ● Sequences are automatically cleaned, trimmed, size selected and mapped directly to miRNA hairpin sequences ● Identifies epi-transcriptomic modifications in the input sequences. ● Alignment with BLAST to miRbase and differential Expression of miRNAs using Deseq2 ● Modification profiles of 3’ and 5’ and internal modifications, uridylation, adenylation and internal modifications or variations of the miRNAs. |
2015 | Dimitrios M. Vitsios et all. | Bioinformatics [URL] 10.1093/ bioinformatics/ btv380 |
| miRTOP | Standalone Linux |
● Generation of a new file format mirGFF3. ● It is compatible with the commonly used tools output files (sRNAbench, Prost!, isomiR-SEA, OptimiR e.g.). ● Converts mirGFF3 file into several different types such as count matrix, FASTA and VCF formats. ● Open source and community-based project. |
2019 | Thomas Desvignes et all. | Bioinformatics Open Access [URL] 10.1093/ bioinformatics/ btz675 |
| Prost! | Standalone Linux |
● Aligns reads to a user-defined genomic dataset. ● Groups reads based on their potential genomic origins, seed sequence and annotation. ● Reports frequencies of individual sequence variations with respect to reference genome and the most expressed sequence. ● Uses Cutadapt and FASTX-toolkit for preprocessing, BBMap suite for alignment, MirBase for annotation and Deseq2 for differential expression. |
2019 | Thomas Desvignes et all. | Nature Open Access [URL] 10.1038/ s41598-019- 40361-8 |
| OptimiR | Standalone Linux |
● Detect genotyping errors ● Suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers. ● Uses Cutadapt for preprocessing, Bowtie2 for alignment and miRBase for annotation. ● Uses a scoring algorithm to identify the most plausible alignments. ● Produces a comparison analysis of genotype data provided by the user and the genotype data that could be inferred from the sequenced reads aligned to polymiRs |
2019 | Florian Thibord et all. | Bioinformatics Open Access [URL] 10.1261/ rna.069708.118 |
| isomiRs: Analyze isomiRs and miRNAs from small RNA-seq | R library | ● Uses as input file the count matrix ● Includes various functions for characterization of miRNAs and isomiRs, clustering, differential expression and visualizations. ● Designed to analyze the output of SeqBuster tool or any other tool after converting to the desire format ● user can control the analysis step by step. |
2020 | Pantano L, Escaramis G | Bioconductor [URL] 10.18129/ B9.bioc.isomiRs |