# miRmap - Comprehensive prediction of microRNA target repression strength
The *miRmap* library is a Python library predicting the repression strength of microRNA (miRNA) targets. The model combines:
- **thermodynamic** features: *ΔG duplex*, *ΔG binding*, *ΔG seed duplex*, *ΔG seed binding*, *ΔG open* and *ΔG total*,
- **evolutionary** features: *BLS* and *PhyloP*,
- **probabilistic** features: *P.over binomial* and *P.over exact*, and
- **sequence-based** features: *AU content*, *UTR position* and *3' pairing*.
> **NOTE** This is a reimplementation by the same author of the miRmap library published in 2011 with most of the core algorithm unchanged. Please refer to the [miRmap1](https://git.sr.ht/~vejnar/miRmap1) repository for the old library.
## Online
*miRmap* is available [online](https://mirmap.ezlab.org).
## Download
See [refs](https://git.sr.ht/~vejnar/miRmap/refs) page.
## Citation
If you use miRmap for your research, please cite:
> Charles E. Vejnar and Evgeny M. Zdobnov<br>
> miRmap: Comprehensive prediction of microRNA target repression strength<br>
> Nucleic Acids Research 2012 Dec 1;40(22):11673-83. doi: [10.1093/nar/gks901](https://doi.org/10.1093/nar/gks901)
## Installation
### External dependencies
1. The [Spatt](https://nuel.perso.math.cnrs.fr/spatt) library is necessary for the *P.over exact* feature.
Download the latest [Spatt](https://nuel.perso.math.cnrs.fr/spatt) tarball (Version 2.1 was successfully tested), then do:
```bash
cd spatt-<version>
mkdir build
cd build
cmake -DWITH_SHARED_LIB=ON ..
make
```
To create the library at `libspatt2/libspatt2.so`.
2. [PHAST](http://compgen.bscb.cornell.edu/phast) is necessary for the evolutionary features. Compilation instructions of PHAST are available in this [PKGBUILD](https://aur.archlinux.org/cgit/aur.git/tree/PKGBUILD?h=phast).
### Using `pip`
After installing external dependencies, install *miRmap*:
```bash
pip3 install mirmap
```
Python dependencies [ViennaRNA](https://pypi.org/project/ViennaRNA) and [dendropy](https://pypi.org/project/DendroPy) will be installed from [PyPI](https://pypi.org/).
## Example
```python
import mirmap.target
utr_seq = "ATAGACTGTACATTATGAAGAATACCCAGGAAGACTTTGTGACTGTCACTTGCTGCTTTTTCTGCGCTTCAGTAACAAGT"
mirna_seq = "UAGCAGCACGUAAAUAUUGGCG".replace("U", "T")
targets = mirmap.target.find_targets_with_seed(utr_seq, mirna_seq)
print(targets[0].report())
``````
This will return:
```
36 57
| |
CAGGAAGACTTTGTGACTGTCACTTGCTGCTTTTTCTGCGCT
|||||||
GCGGTTATAAATGCACGACGAT
```
Then we can calculate the scores of the miRNA target:
```python
import mirmap.if_lib_spatt
import mirmap.scores
if_spatt = mirmap.if_lib_spatt.Spatt("bin/linux_x86_64/libspatt2.so")
scores = mirmap.scores.calc_scores(
targets[0],
if_spatt=if_spatt,
)
print(mirmap.scores.report_scores(scores))
```
This will return:
```
ΔG duplex (kcal/mol) -13.8
ΔG binding (kcal/mol) -11.95
ΔG open (kcal/mol) 14.03
ΔG total (kcal/mol) 0.2345
AU content 0.6574
UTR position 22.0
3' pairing 1.0
TargetScan score 23.66
Probability (Exact) 0.03813
Probability (Binomial) 0.006405
Conservation (BLS) 0.0
Conservation (PhyloP) 1.0
miRmap score -0.3122
```
## License
The *miRmap* library is distributed under the GNU GPL v3 (see /LICENSE).
Copyright © 2011-2024 Charles E. Vejnar
Raw data
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"description": "# miRmap - Comprehensive prediction of microRNA target repression strength\n\nThe *miRmap* library is a Python library predicting the repression strength of microRNA (miRNA) targets. The model combines:\n\n - **thermodynamic** features: *\u0394G duplex*, *\u0394G binding*, *\u0394G seed duplex*, *\u0394G seed binding*, *\u0394G open* and *\u0394G total*,\n - **evolutionary** features: *BLS* and *PhyloP*,\n - **probabilistic** features: *P.over binomial* and *P.over exact*, and\n - **sequence-based** features: *AU content*, *UTR position* and *3' pairing*.\n\n> **NOTE** This is a reimplementation by the same author of the miRmap library published in 2011 with most of the core algorithm unchanged. Please refer to the [miRmap1](https://git.sr.ht/~vejnar/miRmap1) repository for the old library.\n\n## Online\n\n*miRmap* is available [online](https://mirmap.ezlab.org).\n\n## Download\n\nSee [refs](https://git.sr.ht/~vejnar/miRmap/refs) page.\n\n## Citation\n\nIf you use miRmap for your research, please cite:\n\n> Charles E. Vejnar and Evgeny M. Zdobnov<br>\n> miRmap: Comprehensive prediction of microRNA target repression strength<br>\n> Nucleic Acids Research 2012 Dec 1;40(22):11673-83. doi: [10.1093/nar/gks901](https://doi.org/10.1093/nar/gks901)\n\n## Installation\n\n### External dependencies\n\n1. The [Spatt](https://nuel.perso.math.cnrs.fr/spatt) library is necessary for the *P.over exact* feature.\n\n Download the latest [Spatt](https://nuel.perso.math.cnrs.fr/spatt) tarball (Version 2.1 was successfully tested), then do:\n\n ```bash\n cd spatt-<version>\n mkdir build\n cd build\n cmake -DWITH_SHARED_LIB=ON ..\n make\n ```\n\n To create the library at `libspatt2/libspatt2.so`.\n\n2. [PHAST](http://compgen.bscb.cornell.edu/phast) is necessary for the evolutionary features. Compilation instructions of PHAST are available in this [PKGBUILD](https://aur.archlinux.org/cgit/aur.git/tree/PKGBUILD?h=phast).\n\n### Using `pip`\n\nAfter installing external dependencies, install *miRmap*:\n```bash\npip3 install mirmap\n```\n\nPython dependencies [ViennaRNA](https://pypi.org/project/ViennaRNA) and [dendropy](https://pypi.org/project/DendroPy) will be installed from [PyPI](https://pypi.org/).\n\n## Example\n\n```python\nimport mirmap.target\n\nutr_seq = \"ATAGACTGTACATTATGAAGAATACCCAGGAAGACTTTGTGACTGTCACTTGCTGCTTTTTCTGCGCTTCAGTAACAAGT\"\nmirna_seq = \"UAGCAGCACGUAAAUAUUGGCG\".replace(\"U\", \"T\")\n\ntargets = mirmap.target.find_targets_with_seed(utr_seq, mirna_seq)\nprint(targets[0].report())\n``````\nThis will return:\n```\n 36 57\n | |\nCAGGAAGACTTTGTGACTGTCACTTGCTGCTTTTTCTGCGCT\n |||||||\n GCGGTTATAAATGCACGACGAT\n```\nThen we can calculate the scores of the miRNA target:\n```python\nimport mirmap.if_lib_spatt\nimport mirmap.scores\n\nif_spatt = mirmap.if_lib_spatt.Spatt(\"bin/linux_x86_64/libspatt2.so\")\n\nscores = mirmap.scores.calc_scores(\n targets[0],\n if_spatt=if_spatt,\n)\nprint(mirmap.scores.report_scores(scores))\n```\nThis will return:\n```\n \u0394G duplex (kcal/mol) -13.8\n \u0394G binding (kcal/mol) -11.95\n \u0394G open (kcal/mol) 14.03\n \u0394G total (kcal/mol) 0.2345\n AU content 0.6574\n UTR position 22.0\n 3' pairing 1.0\n TargetScan score 23.66\n Probability (Exact) 0.03813\n Probability (Binomial) 0.006405\n Conservation (BLS) 0.0\n Conservation (PhyloP) 1.0\n miRmap score -0.3122\n```\n\n## License\n\nThe *miRmap* library is distributed under the GNU GPL v3 (see /LICENSE).\n\nCopyright \u00a9 2011-2024 Charles E. Vejnar\n",
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