A module to analyze multiple seqs (information content, frequency, ...)
npm install stat.seqs
> A module to analyze multiple seqs (information content, frequency, ...)
npm install stat.seqs``javascript`
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.
`
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 } ]
`
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 ]
`
`
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
`
`
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);
(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})
`
`
stats.maxLength()
> 4
stats.gaps() // relative percentage of gaps for a column
> [0, 0, 0, 0]
`
stats.addSeq("AAA")
stats.addSeqs(["AAA", "AAB"])
stats.resetSeqs(["AAA", "AAB"])
stats.removeSeq("AAA")
stats.removeSeq(2) // you can also use indexes
Please submit all issues and pull requests to the greenify/stat.seqs repository!
If you have any problem or suggestion please open an issue here.
The MIT License
Copyright (c) 2014, greenify
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