Requirements

miReader is written in java and need

1. Java 5 or greater.
2. QT4 (for GUI vesrion)
3. Any Linux/Windows distribution (x86_64)

1. To run GUI of miReader on Linux or Windows O.S install qt4 (ubuntu user can install qt4 using the command "sudo apt-get install libqt4-dev"). Download QT4 from http://qt-project.org/downloads and install.
2. If you want to run miReader on command line please skip firststep
3. To install java download java from http://www.java.com/en/download/manual.jsp?locale=en (ubuntu user can install using command "sudo apt-get install open-jdk" ).

File format

File format can be either in Fastq or Fasta formats other formats are not supported.

How to Run miReader

On Linux O.S

GUI version of miReader: Extract or unzip the miReader_Linux.tar.gz file, to run miReader execute ./install (need not to be root) this file will create a binary named miReader. Double click on this binary will show a splash screen and after few seconds will show user interface. Select input file, output folder and number of processors, choose model organism out of 5 organism by clicking on radiobutton.

Command Line Interface (CLI) version of miReader: Extract miReader_Linux.tar.gz and execute "java -jar miReader_dicot.jar inputfile (can be in fasta format or in fastq format) output_folder_destination (/home/user/...) number_of_processors" (without quotes).

On Windows O.S

GUI version on windows O.S: Extract the miReader_windows.rar file double click on miReader and follow the above steps to choose input file output folder destination, number of processor and model species.

CLI version: Follow the above steps described to run CLI version of miReader in Linux.

Example for CLI vesrion of miReader: run java -jar miReader_dicot.jar inputfile output_folder number_of_processors if you want to use dicot (Arabidopsis) as model.
Or java -jar miReader_human.jar inputfile output_folder number of processors to identify reads for human model.

NOTE: to run miReader for different model species in above command replace the jar file with respective model
1. miReader_dicot.jar : model - Arabidopsis thaliana
2. miReader_monocot.jar : model - Oryza satvia
3. miReader_human.jar : model - Homo sapiens
4. miReader_nematod.jar : model - Caenorhabditis elegans
5. miReader_fly.jar : model - Drosophila melanogaster

Result

miReader classifier scans the duplexes and classifies the duplexes into a true miRNA duplex and non miRNA duplex, the result file conatins the duplexes with their respective scores in tab seprated format. Scores can vary from 0 to 1 true candidates will have score greater than 0.5 where as negative candidates wil have score less than 0.5. Scores shows that how a candidate duplex is classified by the classifier, higher the score (>0.9 or 1.0) the better is the candidate.