scaSectorID Module¶

The scaSectorID script does the preliminaries of sector identification and stores the outputs using the python tool pickle:

Chooses \(k_{max}\) (the number of significant eigenmodes) by comparison of the \(\tilde{C_{ij}}\) eigenspectrum to that for the randomized matrices
Rotates the top \(k_{max}\) eigenvectors using independent components analysis
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.
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
On:	8.19.2014