E-Predict 1.0 – Microarray-based Species Identification

E-Predict 1.0

:: DESCRIPTION

E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a set of clinical samples and discuss its relevance to other metagenomic applications.

::DEVELOPER

DeRisi Lab, UCSF

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Apache
Perl

:: DOWNLOAD

E-Predict

:: MORE INFORMATION

Citation

Urisman A, Fischer KF, Chiu CY, Kistler AL, Beck S, Wang D, DeRisi JL.
E-Predict: A Computational Strategy for Species Identification Based on Observed DNA Microarray Hybridization Patterns.
Genome Biology 2005, 6:R78

specI 1.0 – Species Identification tool

specI 1.0

:: DESCRIPTION

specI is a method to group organisms into species clusters based on 40 universal, single-copy phylogenetic marker genes.

::DEVELOPER

Bork Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python
Perl
usearch
glsearch

:: DOWNLOAD

specI

:: MORE INFORMATION

Citation

Nat Methods. 2013 Sep;10(9):881-4. doi: 10.1038/nmeth.2575. Epub 2013 Jul 28.
Accurate and universal delineation of prokaryotic species.
Mende DR1, Sunagawa S, Zeller G, Bork P.

Clarki 20090715 – Use SNP data for Species Identification

Clarki 20090715

:: DESCRIPTION

Clarki estimate the composition of hybrids using SNP and other diallelic loci that have fixed differences between taxa.

::DEVELOPER

Steven Kalinowski, Ph.D.

:: SCREENSHOTS

::REQUIREMENTS

Windows
.NET platform

:: DOWNLOAD

Clarki

:: MORE INFORMATION

Citation

Kalinowski ST (2009)
How to uses SNPs and other diagnotic diallelic genetic markers to estimate the composition of multi-species hybrids.
Conservation Genetics Resources, Volume 2, Number 1, December 2010 , pp. 63-66(4)