scaCore Module

scaTools Module

# scaSectorID Module¶

The scaSectorID script does the preliminaries of sector identification and stores the outputs using the python tool pickle:
1. Chooses $$k_{max}$$ (the number of significant eigenmodes) by comparison of the $$\tilde{C_{ij}}$$ eigenspectrum to that for the randomized matrices
2. Rotates the top $$k_{max}$$ eigenvectors using independent components analysis
3. Defines the amino acid positions that significantly contribute to each of the independent components (ICs) by empirically fitting each IC to the t-distribution and selecting positions with greater than a specified cutoff (default: p=0.95) on the CDF.
4. Assign positions into groups based on the independent component with which it has the greatest degree of co-evolution.
Arguments:

*.db (the database produced by running scaCore.py).

Keyword Arguments:

 --kpos, -k number of significant eigenmodes for analysis (the default is to automatically choose using the eigenspectrum) --cutoff, -p empirically chosen cutoff for selecting AA positions with a significant contribution to each IC, Default = 0.95 --matlab, -m write out the results of this script to a matlab workspace for further analysis
Example:
>>> ./scaSectorID.py PF00071_full.db

By: Kim Reynolds 8.19.2014