stat.seqs

A module to analyze multiple seqs (information content, frequency, ...)

Getting Started

Install the module with: npm install stat.seqs

var MSAStats = require('stat.seqs');
var seqs = ["AACG", "CACG", "AAGC", "CAAG"];
var stats = MSAStats(seqs);

All operations are cached, but they will be calculated again if you change the sequences.

Operations

Frequency

stats.frequency() // calculates the relative frequency of a base at a given position
> [ { A: 0.5, C: 0.5 },
  { A: 1 },
  { C: 0.5, G: 0.25, A: 0.25 },
  { C: 0.25, G: 0.75 } ]

Sequence identity and consensus

stats.consensus() // calculates the consensus
> "AACG"

stats.identity() // identity to the consensus seq
> [ 1, 0.75, 0.5, 0.5 ]

stats.identity("AAAA") // identity to the given seq
> [ 0.5, 0.25, 0.5, 0.5 ]

Background distribution

stats.background() // calculates the background distribution of all seqs
> { A: 0.4375, C: 0.3125, G: 0.25 }

stats.bg = {A: 0.25, C: 0.25, G: 0.25, T: 0.25} // set your own background distribution

stats.useBackground(); // use background distribution in anlysis

Information content (entropy) and conservation

stats.ic() // calculates the information content
> [ 1, 0, 1.5, 0.81 ]

// change your alphabet
stats.setDNA(); // default
stats.setProtein();
stats.alphabetSize = 21; // your own size

// now you can scale the information content 
stats.scale(stats.ic());
> [ 0.5, 0, 0.75, 0.41 ]

stats.conservation() // needs an alphabetSize!
> [ 1, 2, 0.5, 1.19 ]
stats.scale(stats.conservation()) // scale conservation 
> [ 0.5, 1, 0.25, 0.59 ]

stats.conservResidue() // calculate conservation per residue
> [ { A: 0.5, C: 0.5 },
  { A: 2 },
  { C: 0.25, G: 0.13, A: 0.13 },
  { G: 0.89, C: 0.3 } ]

stats.conservResidue({scaled: true}) 
> [ { A: 0.25, C: 0.25 },
  { A: 1 },
  { C: 0.13, G: 0.06, A: 0.06 },
  { G: 0.45, C: 0.15 } ]

Scale and conservation require a set alphabetSize (default 4);

Conservation with a background distribution

(work in progress)

stats.useBackground(); // by default from all letters

stats.ic() // calculates the information content
stats.scale(stats.ic());

stats.conservation(

stats.scale(stats.conservation())

stats.conservResidue() 

stats.conservResidue({scaled: true}) 

Trivial analysis

stats.maxLength() 
> 4
stats.gaps() // relative percentage of gaps for a column
> [0, 0, 0, 0]

Operate with the sequences

stats.addSeq("AAA")
stats.addSeqs(["AAA", "AAB"])
stats.resetSeqs(["AAA", "AAB"])
stats.removeSeq("AAA")
stats.removeSeq(2) // you can also use indexes

Contributing

Please submit all issues and pull requests to the greenify/stat.seqs repository!

Support

If you have any problem or suggestion please open an issue here.

License

The MIT License

Copyright (c) 2014, greenify

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.