Metadata-Version: 1.1
Name: premirnaplot
Version: 0.7
Summary: pre-miRNA secondary structure prediction image generator
Home-page: https://github.com/igrorp/pre-miRNA-plot
Author: Igor Paim
Author-email: igorpaim8@gmail.com
License: GPL
Description: 
         python3+ premiRNA-plot.py [INPUTS] ... [OPTIONS] ...
        
        -----------------------------------------------------------------------------------------
        
        Pre-miRNA-plot is a program for generating multiple custom images of miRNA precursors based
        on RNAfold and RNAplot. It allows you to highlight the miRNA location within the precursor
        and obtain general and practical information about your data, so you can filter it or use
        it in publications.
        
        -----------------------------------------------------------------------------------------
        
        The program accepts tab-separated text files containing possibly 4 columns:
        
        	1) Sequence ID (optional): Some sort of annotation or ID
        		information about the sequence (e.g. 'ath-miR-171' or 'seq1');
        	2) Precursor sequence: The pre-miRNA sequence.
        	3) miRNA1 sequence: One of the miRNAs sequences.
        	4) miRNA2 sequence (optional): The other miRNA sequence.
        
        	File format examples:
        
        	| pre-miRNA |   miRNA1   |  miRNA2  |
        
        	>>>>>>>>>>>>>>>>>>>>>> OR <<<<<<<<<<<<<<<<<<<<<<<
        
        	|     ID    |  pre-miRNA |  miRNA1  |   miRNA2  |
        
        There is no problem if you don't have both miRNAs sequences;
        you can inform just one and the program will work just fine.
        
        Checkout our github repository for more details on how to use
        the program: https://github.com/igrorp/pre-miRNA-plot
        
        Parameters:
        
        -i, --input       (str ...)
        
        	Inform the names of/paths to the files that you want to use.
        
        -a, --annot       (str) --> (T or F)
        
        	Informs if you have some sort of sequence ID, such as a miRNA
        	family annotation (e.g.'ath-miRNA-171', 'seq1'), necessarily
        	on the first column, so that the generated image files can be
        	named according to that ID.
        
        	Default = F (False)
        
        -s, --style       (int) --> (between 1 and 5)
        
        	The style of created images. Check the repository to see how they
        	look like.
        
        	Default = 3
        
        -c, --color       (str str) OR (int int int int int int)
        
        	You can choose which colors to paint the miRNA sequence within
        	the precursor. Always provide the 5p and 3p colors, respectively.
        	You can choose the predefined color names blue, red, green, purple,
        	pink, yellow, cyan, white, black and orange; or you can inform the
        	RGB codes of the colors you want.
        
        	Ex: '-c blue green' for blue 5p and green 3p
        	Ex: '-c 255 255 0 153 0 204' for yellow 5p and purple 3p
        	Default = green and red
        
        -t, --threads     (int)
        
        	Choose the number of allowed processors (CPUs) to be used.
        
        	Default = 1
        
        -f, --formats     (str) --> (svg or pdf)
        
        	Choose the output format of the images. Choose between PDF and SVG.
        
        	Default = svg
        
        -o, --outdir      (str)
        
        	The output name of directory created containing all the generated data.
        
        	Default = premirnaplot
        
        
        
        ---------------------------------------------------------------
        
        If you have any comments, complaints, doubts or suggestions, please contact
        our main responsible for this project at igorpaim8@gmail.com or create an issue in
        out github repository https://github.com/igrorp/pre-miRNA-plot/issues.
        
        Have a nice work and let's keep making science evolve!
        
        
Keywords: pre-miRNA
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python :: 3
