Back

miRScore: a rapid and precise microRNA validation tool

Vanek, A.; Griffiths-Jones, S. J.; Meyers, B. C.; Shahid, S.; Axtell, M. J.

2024-12-17 bioinformatics
10.1101/2024.12.12.628184 bioRxiv
Show abstract

MicroRNAs (miRNAs) are small non-protein-coding RNAs that regulate gene expression in many eukaryotes. Next-generation sequencing of small RNAs (small RNA-seq) has accelerated discovery and annotation of novel miRNAs. Newly discovered miRNAs are typically submitted to databases such as the miRBase microRNA registry following the publication of a peer-reviewed study. However, genome-wide scans using small RNA-seq data often yield high rates of false-positive miRNA annotations, highlighting the need for more robust validation methods. miRScore was developed as an independent and efficient tool for evaluating miRNA annotations using sRNA-seq data. miRScore combines structural and expression-based analyses to provide rapid and reliable validation of miRNA annotations. By providing users with detailed metrics and visualization, miRScore enhances the ability to assess confidence in novel and existing miRNA annotations. miRScore has the potential to advance the overall quality of miRNA annotations by improving accuracy of new submissions to miRNA databases and serving as a resource for re-evaluating existing annotations.

Published in PLOS Computational Biology (predicted rank #18) · training set

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nucleic Acids Research
◐ 1281 papers in training set
Top 1%
12.5%
Similar papers in this journal
2
BMC Bioinformatics
○ 457 papers in training set
Top 0.5%
11.7%
Similar papers in this journal
3
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 0.2%
9.5%
Similar papers in this journal
4
PLOS ONE
● 5266 papers in training set
Top 20%
8.7%
Similar papers in this journal
5
BMC Genomics
○ 406 papers in training set
Top 0.6%
7.1%
Similar papers in this journal
6
Scientific Reports
○ 3612 papers in training set
Top 13%
6.1%
50% of probability mass above
7
RNA
● 189 papers in training set
Top 0.4%
5.5%
8
RNA Biology
○ 78 papers in training set
Top 0.2%
5.1%
9
Bioinformatics
◐ 1204 papers in training set
Top 5%
4.2%
10
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 3%
1.9%
11
PeerJ
◐ 308 papers in training set
Top 5%
1.7%
12
Genome Biology
○ 637 papers in training set
Top 6%
1.7%
13
Briefings in Bioinformatics
◐ 354 papers in training set
Top 5%
1.7%
14
F1000Research
○ 88 papers in training set
Top 2%
1.5%
15
GigaScience
◐ 212 papers in training set
Top 3%
1.5%
16
G3 Genes|Genomes|Genetics
◐ 351 papers in training set
Top 3%
1.4%
17
Plant Methods
○ 42 papers in training set
Top 0.6%
1.1%
PLOS Computational Biology · published here
● 1863 papers in training set
Top 17%
1.1%
19
Plant Direct
○ 95 papers in training set
Top 2%
1.0%
20
Bioinformatics Advances
◐ 203 papers in training set
Top 4%
1.0%
21
The CRISPR Journal
○ 39 papers in training set
Top 0.4%
0.8%
22
Plant Physiology
◐ 238 papers in training set
Top 3%
0.6%
23
Genes
○ 144 papers in training set
Top 5%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.