This code repository accompanies the manuscript

*An Evolutionary Trace method defines functionally
important bases and sites common to RNA families*

There are two components of interest

1. ET program (ET_RNA_ms/et_bin/wetc) stand-alone C binary that produces ET ranking given a MSF alignment

   To run:

   1. In terminal, navigate to ET_RNA_ms/et_bin/

   2. Ensure the program runs by typing "./wetc - help"

   3. To score an RNA aligment, type

      ./wetc -p [aln_path] -x [query_seq_name] -dnaet -realval -o [output_name]

      -p path to MSF alignment -x name of the query sequence as it appears in the alignment -dnaet flag to enable non-protein scoring -realval flag to run rvET scoring -o base name for output files (can pipe it directly into dir '-o dir_path/basename')

2. Example of RNAse P analysis, wrapped in MATLAB.

   To run:

   1. Launch MATLAB

   2. Navigate MATLAB console to ET_RNA_ms/rnasep_example/

   3. Execute script 'rnasep_demo.m' by typing 'rnasep_demo'

   4. The script will:

      a. Load msf alignment of RNAse P homologues

      b. Load RNAse P structure 3q1q (chain B)

      c. Calculate adjacency matrix for 3q1q (chain B)

      d. Profile sequence of chain B to the MSF alignment as query

      e. Trace the profile alignment (outputs are saved to ../et_temp/, then mv'ed to ./results)

      f. Calculate random expected clustering for adj matrix

      g. Calcuate clustering by ET nucleotides (across bins 0-100).

      h. Calculate overlap of ET nucleotides with functional sites

      i. Print summary tables and figures to ./results and ./visualization

   5. The necessary inputs for this script are in ./input_data/ and include:

      1. MSF alignment of RNAse P homologues
      2. 3Q1Q pdb file

3. Possible Errors:

   1. Make sure gaps are denoted as '.' in the MSF alignment
   2. If using wetc standalone, make sure the file path in -o is not too long (will throw error)

Bonus:

Ribosome Example (ET_RNA_ms/ribosome_23S_example) example of ET application using the 23S rRNA alignment, including the ET trace, and z-score computations (Several intermediate steps here are already pre-computed)

To run:

1. Launch matlab
2. Navigate in matlab console to ET_RNA_ms/ribosome_23S_example
3. Type 'ls' (no quotes) to examine contents of folder, there are 3 scripts of interest trace_alignment.m traces the 16S alignment measure_et_structural_clustering calculates ET clustering in the 16S structure measure_et_prediction_accuracy calculates ET overlap with know functional sites in 16S
4. Execute these 3 scripts in order
5. Results and plots will be in the results/ and visualizaion/ folders

Dependencies: The code was tested on MATLAB v2017b with Bioinformatics toolbox.