Evidence map›Paper›PMID 34308351›Full record

ArticleNAR genomics and bioinformatics2021

miRge3.0: a comprehensive microRNA and tRF sequencing analysis pipeline.

Arun H Patil, Marc K Halushka

Open access · goldAbstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed
5.2field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

61 citing papers in PubMed, 81 citations in OpenAlex.

  1. Review
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  13. MicroRNAs and Their Profiling via Single-Cell Sequencing Technologies.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  14. Article
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  18. Article
  19. IsomiR stoichiometry changes as disease biomarkers.Molecular therapy. Nucleic acids · 2025
    Article
  20. Article

1 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Arun H PatilDepartment of Pathology, Division of Cardiovascular Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Marc K HalushkaDepartment of Pathology, Division of Cardiovascular Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.ORCID https://orcid.org/0000-0002-7112-7389
Johns Hopkins University · US

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI ALAN KEITH MEEKER · 1985 to 2026
$208.6M
Fine Dissection of Atherosclerosis Microenvironment RNA ExpressionR01HL137811 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI HALUSHKA, MARC K · 2017 to 2020
$2.4M
xMD-miRNA-Seq estimates cell-specific miRNA expressionR01GM130564 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI HALUSHKA, MARC K · 2018 to 2021
$1.2M
NCI NIH HHS P30 CA006973NHLBI NIH HHS R01 HL137811NIGMS NIH HHS R01 GM130564
6 · The paper itself

Abstract

MicroRNAs and tRFs are classes of small non-coding RNAs, known for their roles in translational regulation of genes. Advances in next-generation sequencing (NGS) have enabled high-throughput small RNA-seq studies, which require robust alignment pipelines. Our laboratory previously developed miRge and miRge2.0, as flexible tools to process sequencing data for annotation of miRNAs and other small-RNA species and further predict novel miRNAs using a support vector machine approach. Although miRge2.0 is a leading analysis tool in terms of speed with unique quantifying and annotation features, it has a few limitations. We present miRge3.0 that provides additional features along with compatibility to newer versions of Cutadapt and Python. The revisions of the tool include the ability to process Unique Molecular Identifiers (UMIs) to account for PCR duplicates while quantifying miRNAs in the datasets, correct erroneous single base substitutions in miRNAs with miREC and an accurate mirGFF3 formatted isomiR tool. miRge3.0 also has speed improvements benchmarked to miRge2.0, Chimira and sRNAbench. Finally, miRge3.0 output integrates into other packages for a streamlined analysis process and provides a cross-platform Graphical User Interface (GUI). In conclusion miRge3.0 is our third generation small RNA-seq aligner with improvements in speed, versatility and functionality over earlier iterations.

Identifiers

PMID34308351
PMCPMC8294687
OpenAlexW3184307727

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.