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https://github.com/arr4n/compressgv

DEFLATE compression algorithm corrects for overestimation of phylogenetic diversity by Grantham approach to single-nucleotide polymorphism classification
https://github.com/arr4n/compressgv

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DEFLATE compression algorithm corrects for overestimation of phylogenetic diversity by Grantham approach to single-nucleotide polymorphism classification

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README 

        
#CompressGV



[Citation](#citation) | [Abstract](#abstract) | [Browser & HTTP Interface](#browser--http-interface) | [Requirements](#requirements) | [Installation](#installation)



##Citation



Schlosberg A, Lam BYH, Yeo GSH, Clifton-Bligh RJ. DEFLATE Compression Algorithm Corrects for Overestimation of Phylogenetic Diversity by Grantham Approach to Single-Nucleotide Polymorphism Classification. *International Journal of Molecular Sciences*. 2014; 15(5):8491-8508.



[Read online - Open Access](http://dx.doi.org/10.3390/ijms15058491)



##Abstract



**Background:** Improvements in speed and cost of genome sequencing are resulting in increasing numbers of novel non-synonymous single nucleotide polymorphisms (nsSNPs) in genes known to be associated with disease. The large number of nsSNPs makes laboratory-based classification infeasible and familial co-segregation with disease is not always possible. *In-silico* methods for classification or triage are thus utilised. A popular tool based on multiple-species sequence alignments (MSAs), Align-GVGD, has been shown to underestimate deleterious effects, particularly as sequence numbers increase.



**Results:** We utilised the DEFLATE compression algorithm to account for expected variation across a number of species. With the adjusted Grantham measure we derived a means of quantitatively clustering known neutral and deleterious nsSNPs from the same gene; this was then used to assign novel variants to the most appropriate cluster as a means of binary classification. Scaling of clusters allows for inter-gene comparison of variants through a single pathogenecity score.



**Conclusions:** The approach improves upon the classification accuracy of Align-GVGD while correcting for sensitivity to large MSAs.



##Browser & HTTP Interface



A server running CompressGV is made available for anonymous usage; input data is destroyed immediately after classification and output is not stored. A [browser-based interface](http://compressgv.arranschlosberg.com) is available for standard users. Low-volume [usage directly over HTTP](http://compressgv.arranschlosberg.com/#help) is encouraged for personal use only.



##Requirements



Versions in brackets refer to those used in development; earlier versions may be compatible but have not been tested.



* [GNU Scientific Library](http://www.gnu.org/software/gsl/) + CBLAS (1.16)

* [zlib](http://www.zlib.net/) (1.2.8)

* [PSO](https://github.com/aschlosberg/pso) implementation ([kkentzo/pso 5a992b312e](https://github.com/kkentzo/pso/commit/5a992b312e21c421b363ed95cf5b0f7dede9890a))



##Installation



A sample Linux makefile is included.



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Copyright 2014 Arran Schlosberg.



This file is part of https://github.com/aschlosberg/CompressGV (CompressGV)



    CompressGV is free software: you can redistribute it and/or modify

    it under the terms of the GNU General Public License as published by

    the Free Software Foundation, either version 3 of the License, or

    (at your option) any later version.



    CompressGV is distributed in the hope that it will be useful,

    but WITHOUT ANY WARRANTY; without even the implied warranty of

    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

    GNU General Public License for more details.



    You should have received a copy of the GNU General Public License

    along with CompressGV. If not, see .



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