Scripts and Data for the 2019 IPAM Women in Biology Workshop Project in RNA Ensemble Analysis

Description

This repository contains the scripts created for the 2019 IPAM Women in Biology Workshop Project in RNA Ensemble Analysis as well as the resulting data. ipam-fun.py is the main script, although many of the other files are runnable. Graph based clustering is performed on filtered sampled RNA secondary structural ensembles to identify important clusters of features. The output for various sequences as well as the sampled ensembles are in the Data folder. For more details, please see the associated book chapter (link will be made available).

Dependencies

These scripts are written for Python 3 and untested with 2.*. They are known to work with Python 3.6, although they likely are functional with earlier versions. The Numpy, Scipy, Matplotlib, and NetworkX python packages are required. The scripts are dependent on two other software projects. Ensemble sampling is performed using the Mathews Lab RNAstructure ensemble sampling component. The ensemble data is filtered and summarized using RNAProfiling. The compiled RNAProfiling executable must be placed in a parallel directory to ipam-wbio-scripts. If this git repository was cloned to ~/Documents/replication/ipam-wbio-scripts then there must be an executable ~/Documents/replication/src/RNAprofile.

Usage

To run, use the ipam-fun.py script. For example, if B0000234_seq.txt is a file containing a tRNA sequence and RNAStructure is placed on the user's desktop:

python3 ipam-fun.py ~/tRNA/B0000234/B0000234_seq.txt ~/Desktop/RNAStructure/

It is important that the sequence files be of the form *_seq.txt. The script should work with either absolute or relative paths to the sequence file. An optional third argument is a file which contains line separated integer seeds. If this is not provided, then the number 1 is used as a single seed.

Data

For each sequence used in the final analysis, we provide the sequence, sampled ensemble, RNAProfiling output, visualization of the clusters, a text file containing the clusters, and a file containing a description of the clusters and experimental parameters used to run the scripts.