MicroRNAs, or miRNAs, post-transcriptionally repress the expression of protein-coding genes. The human genome encodes over 1000 miRNA genes that collectively target the vast majority of messenger RNAs (mRNAs). Base-pairing of the so-called miRNA “seed” region with mRNAs identifies many thousands of putative targets. Evaluating the strength of the resulting mRNA repression remains challenging, but is essential for a biologically informative ranking of potential miRNA targets. To address these challenges, predictors may employ thermodynamic, evolutionary, probabilistic, or sequence-based features. We developed an open source software library, miRmap, which for the first time comprehensively covers all four approaches using eleven predictor features, three of which are novel. This allowed us to examine feature correlations and to compare their predictive power in an unbiased way using high throughput experimental data from immunopurification, transcriptomics, proteomics and polysome fractionation experiments. Overall, target site accessibility appears to be the most predictive feature. Our novel feature based on PhyloP, which evaluates the significance of negative selection, is the best performing predictor in the evolutionary category. We combined all the features into an integrated model that almost doubles the predictive power of TargetScan.
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User-friendly and feature-rich miRmap web application.
- Start the tutorial here.
- Requires Firefox >= 4 or Internet Explorer >= 8 or Chrome.
Programmatic way of accessing miRmap online predictions: all the functionnality of the web interface through a REST interface. See the documentation for more details.
|Release name||Species||Release date||Notes|
Note 1: File name format <release_name>_<species>_<content>.csv.xz
|_targets||All predicted target sites with their genomic and 3'-UTR coordinates|
|_targets_1to1||All miRNA-mRNA predicted regulations|
|_targets_1to1_pt||Same as above, as percentiles over the prediction set|
|_mirnas||miRNA names and sequences|
|_transcripts||mRNA transcripts names and sequences|
Note 2: All CSV files are compressed using Zstandard. The Python Data Analysis Library pandas decompresses Zstandard files transparently.
Bundles including miRmap source code and x86_64 libraries and executables for Vienna RNA, PHAST, and Spatt are available at SourceHut.
Click on the latest version and download the file miRmap-version-x86_64.tar.gz.
miRmap is distributed under the GNU GPL (see documentation). Public repository is hosted at SourceHut and GitHub.
If you find a bug or develop a new feature, please report or submit a pull request.
The documentation for the miRmap library is available here. Installation instructions, along with usage examples, can also be found in these pages.
The documentation for the miRmap web interface is available here. A tutorial describing how to use miRmap web interface is available.
The documentation for the miRmap REST interface is available here.
If you use miRmap in your research, please cite this publication:
Charles E. Vejnar and Evgeny M. Zdobnov
miRmap: Comprehensive prediction of microRNA target repression strength
Nucleic Acids Research 2012 Dec 1;40(22):11673-83. doi: 10.1093/nar/gks901