=========================================================================================== TarPmiR Author: Jun Ding Date: March,19,2016 =========================================================================================== TarPmiR is a miRNA-mRNA binding sites prediction tool, which can utilize miRNA-mRNA binding experiment data such as CLASH. * INSTALLATION -------------------------------------------------------------------------------------------- 1. For Linux user (1) First, you need to install python (recommend: python 2.7.x-64bit), which is already installed by default for most of current Linux systems. If there is no python 2.7 installed, you can download and install python from (http://www.python.org/download/). You can use "python -V" command to check whether python is installed and the version of Python. (2) Second,you also need Tkinter(Python 2) or tkinter(Python 3) module for Python to enable the GUI. You can check (http://tkinter.unpythonic.net/wiki/How_to_install_Tkinter) for installation instructions on Linux. Note: this is optional if you do not use GUI. (3) The following dependent packages are required : a. scikit-learn See here (http://scikit-learn.org/stable/install.html) for installation instructions -------------------------- pip install -U scikit-learn --------------------------- note: If you installed the scikit-learn 0.18, please use the corresponding model (Human_sklearn_0.18.pkl) b. numpy Installation instructions for numpy (http://docs.scipy.org/doc/numpy/user/install.html) ---------------------------- pip install -U numpy ----------------------------- c. scipy Installation instructions for scipy (http://www.scipy.org/install.html) ---------------------------- pip install -U scipy ---------------------------- d. ViennaRNA package Installation instructions for ViennRNA package (http://www.tbi.univie.ac.at/RNA/index.html) ------------------------------ You can download and extract corresponding ViennaRNA package from (http://www.tbi.univie.ac.at/RNA/) CD to the the extracted ViennaRNA package directory ./configure sudo make sudo make install ------------------------------- You can SIMPLY use setup.py script to install --------------------------------------------------------------------------------------- python setup.py install ------------------------------------------------------------------------------------- or double click , then choose run in the terminal. You may need to change the running permission chmod +x setup.py ./setup.py -------------------------------------------------------------------------------------- The setup.py script should setup the software automatically for you. 2. For Windows user (1) First, you need to install python 2.7-64bit, which can be obtained from (https://www.python.org/ftp/python/2.7.9/python-2.7.9.amd64.msi). Please use the python windows installer from the above download package. After finishing downloading, just double click the installer to get python installed. The python Windows installer already included the Tkinter module by default and therefore you do not need to do it manually. (2) The following dependent python packages are required : a. scikit-learn b. numpy c. scipy You can use the setup.py script to install these dependent packages automatically. ------------------------------------------------- Just double click the setup.py it will setup the software automatically for you. ------------------------------------------------- * Execution -------------------------------------------------------------------------------------------------------------------------------------- We also include a 'extend_TarPmiR' in the package, which provides an example showing how to extend the TarPmiR to other data sets or another sets of features. Please check 'How2Extend' for details. A. For Linux user (1) Command Line User a. cd to the directory of the software For example, if you put XXXX under your home directory ( "cd /home/YOURNAME/XXXX") YOURNAME is the your home directory name. b. You can run the software by running the script "TarPmiR" with the following command: ---------------------------------------------------------------------------------------- python TarPmiR.py -a Input microRNA sequences, in FASTA Format -b Input mRNA sequences, in FASTA Format. mRNA id should be Ensembl mRNA ID/ RefSeq mRNA ID -m Prediction model, which you can select from "models" directory (Currently, it's only human, which can be applied to species close to human as well. e.g. Mouse) -p Probability cut, which defines a true miRNA-mRNA binding site. (e.g. 0.5, means that it's a true binding site if the prediction proability >0.5) For example, if we want to predict miRNA-mRNA bindings from the provided example miRNA sequence(miR) and mRNA sequences (mRNAs) located under the directory "example" by Human model, Human.pkl We can use the following command: ---------------------------------------------------------------------------------------- python TarPmiR.py -i example/miR -b example/mRNAs -m models/Human.pkl -p 0.5 -------------------------------------------------------------------------------------------- (2) GUI user Just double click the XXXX_GUI.py and choose "Run in Terminal", you might need to change the permision of TarPmiR_GUI.py by using the following command: --------------------------------------------------- chmod +x TarPmiR_GUI.py --------------------------------------------------- B. For Windows user (1) Command Line User a.open prompt window. Open the Command Prompt window by clicking the Start button , clicking All Programs, clicking Accessories, and then clicking Command Prompt. b.cd to the directory of software c.You can run the software by running the script "TarPmiR.py" with the following command: ---------------------------------------------------------------------------------------- TarPmiR.py -a Input microRNA sequences, in FASTA Format -b Input mRNA sequences, in FASTA Format. mRNA id should be Ensembl mRNA ID/ RefSeq mRNA ID -m Prediction model, which you can select from "models" directory (Currently, it's only human, which can be applied to species close to human as well. e.g. Mouse) -p Probability cut, which defines a true miRNA-mRNA binding site. (e.g. 0.5, means that it's a true binding site if the prediction proability >0.5) For example, if we want to predict miRNA-mRNA bindings from the provided example miRNA sequence(miR) and mRNA sequences (mRNAs) located under the directory "example" by Human model, Human.pkl We can use the following command: ---------------------------------------------------------------------------------------- TarPmiR.py -i example/miR -b example/mRNAs -m models/Human.pkl -p 0.5 -------------------------------------------------------------------------------------------- (2) GUI user Just double click the XXXX_GUI.py and choose "Run in Terminal", you might need to change the permision of TarPmiR_GUI.py by using the following command: --------------------------------------------------- chmod +x TarPmiR_GUI.py --------------------------------------------------- (2) GUI user Just double Click the TarPmiR_GUI.py * Result ---------------------------------------------------------------------------------------------------------------------------------- Result files: X.bp (X will be your input miRNA_name+'_'+mRNA_name under the same folder as your input miRNA file. 1st col: miRNA-name 2nd col: mRNA-name 3rd col: binding-site 4th col: binding_probabiliity The following cols: All features used output example: -------------------------- miRNA mRNA binding_site binding_probability energy seed accessibility AU_content PhyloP_Stem PyloP_Flanking m/e number_of_pairings binding_region_length longest_consecutive_pairings position_of_longest_consecutive_pairings pairings_in_3prime_end difference_of_pairings_between_seed_and_3prime_end hsa-miR-103 ENST00000496239 606,631 0.769230769231 -21.7 0 0.002405382 0.485 0.467609085714 -0.14620110375 -5.69428359855 19 25 9 11 6 0 hsa-miR-103 ENST00000496239 4283,4321 0.846153846154 -21.6 0 0.007585786 0.426 -0.278324883871 0.284277415 -6.96959672116 20 37 8 28 6 1 hsa-miR-103 ENST00000496239 1047,1069 0.769230769231 -20.9 1 1.061299e-06 0.397 0.517852153846 -0.02826825 -8.30380402897 16 22 7 15 4 2 hsa-miR-103 ENST00000496239 1190,1209 0.846153846154 -20.4 0 1.838396e-06 0.426 0.558756857143 -0.050087005 -9.99616657232 15 19 10 9 5 0 hsa-miR-93 ENST00000496239 1952,1999 0.846153846154 -26.7 1 9.098354e-06 0.382 0.1863519 -0.46235441 -12.2551227614 17 23 10 1 6 2 hsa-miR-19b ENST00000496239 2492,2515 0.538461538462 -16.1 0 0.01566448 0.574 -0.614130371429 -0.1769159275 -6.73762038884 18 23 7 12 5 2 -------------------------- When the software is running, you might see "Running..." on the bottom of the GUI, the GUI probably will show "Not Responding", but it's OK. You will see "Done" on the bottom of GUI when results were obtained. * License & Credits ------------------------------------------------------------------------------------------------- The software is a freely available for academic use. This software is using the following packages: Scikit-learn pymysql ViennaRNA It is also available for non-academic use under appropriate licensing. plase contact xiaoman shawn li (xiaoman@mail.ucf.edu) for further information. * Contact info If you are encountering any problem regarding to SIOMICS, please refer the manual first. If problem still can not be solved, please feel free to contact us: Jun Ding (jding@cs.ucf.edu) Nancy Haiyan Hu (haihu@cs.ucf.edu) Xiaoman Shawn Li (xiaoman@mail.ucf.edu)