Python Package for RNA structurome quantification analysis.
CONTENTS AND COPYRIGHT
This package is used for maniputating genome annotation and seqeunce files, such as Bed, GenePred, BAM, Wiggle and BigWig formats. Users interested in this package should contact firstname.lastname@example.org for details. This package uses the Vienna RNA Package lib and H directories (external/RNAlib/fold) and RNAStructure libs (external/RNAlib/plot), and users should read the COPYING or ReadMe.txt files inside and behave accordingly. All files are copyrighted, but license is hereby granted for personal, academic and non-profit use. Commercial users should contact email@example.com.
SOURCES CODES https://pypi.python.org/pypi/rsq
PREREQUISITES 1. python 2.7, python-dev 2. numpy >= 1.4.1 (automatically installed) 3. ngslib >= 1.1.10 for NGS data processing (automatically installed) 4. fisher >= 0.1.4 for fisher exact test ((automatically installed) 4. sfold 2.2 stand-alone executable (http://sfold.wadsworth.org/License_info.html)
GENERAL INSTALL INSTRUCTIONS
- Install from Python Package Index (https://pypi.python.org) > easy_install –prefix=$HOME/local rsq
- Install from source file (including the demo example files) >easy_install –editable –build-directory package_source/ rsq >cd package_source >python setup.py install –prefix=install_path
- sfold 2.2
- Download the stand-alone executable from http://sfold.wadsworth.org/License_info.html
- Run configure file
- >cd SFOLD2.2_HOME >./configure
- Test sfold in command line before use:
- If successful, add sfold binary file to system PATH by:
- Data formats:
- FastD, FastC, FastS and EFastS to represent data used in RSQ.
- Readers for each data format
- Wrappers of a series of RNA secondary structure prediction tools. RNAfold, mfold, UNAFold, sfold, et. al. Note: make sure the command/program is callable in shell before call it in RSQ.
- EM algoritm, Boltzmann sampling, structure distance calculation, et. al.
- Utilites. Temperature conversion, structure format conversion, et. al.
- Used in multiple processing procedures.