/center-star-msa

multiprocessing multiple sequence alignment by center star algorithm

Primary LanguagePythonMIT LicenseMIT

The Center Star Method for MSA

Before the beginning, I recommend you to know some basic of pairwise alignment algorithms such as Needleman-Wunch algorithm because I use to calculate pairwise alignments by Needleman-Wunch.

What is the center star method?

The Center Star Algorithm:

  1. Find Sc maximizing Σic D(Sc, Si ).(Note: Some resources say minimizing)
  2. Iteratively construct the multiple alignment Mc:
    1. Mc={Sc}
    2. Add the sequences in S{Sc} to Mc one by one so that the induced alignment aMc(Sc, Si) of every newly added sequence Si with Sc is optimal. Add spaces, when needed, to all pre-aligned sequences.

What is the running complexity?

Combination(k,2) * O(n^2) = O(k^2 * n^2)

Merging example

AC-BC
DCABC

AC--BC
DCAABC

=

AC--BC
DCA-BC
DCAABC

File format

The format of the input file must be this way;

{matchScore},{mismatchScore},{gapScore}
{sequence1}
{sequence2}
{sequence3}
.
.
.
{sequenceN}

for example; whether matchScore = 1, mismatchScore = -1, gapScore = -4 and four strings, the file should be;

1,-1,-4
MPE
MKE
MSKE
SKE

Usage

python cstar.py inputfile outputfile

TODOs

  • Score matrix support []