GeMS 1.0 – A High Efficient SNP Detection Software

GeMS 1.0

:: DESCRIPTION

GeMS (Genotype Model Selection) is a single nucleotide polymorphism (SNP) detector that works with alignment files of high-throughput sequencing (HTS) data. GeMS calls SNPs based on a statistical model selection procedure and accounts for the aerrors that can occur during genomic sample preparation

::DEVELOPER

Cui Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
C Compiler

:: DOWNLOAD

GeMS

:: MORE INFORMATION

Citation

Na You, Gabriel Murillo, Kang Ning, Xiaoquan Su, Xiaowei Zheng, Jian Xu, Shoudong Zhang, Jiankang Zhu and Xinping Cui.
“SNP calling using genotype model selection on next generation sequencing data“,
Bioinformatics. 2012 Mar 1;28(5):643-50. doi: 10.1093/bioinformatics/bts001.

GEMS – Entropy-scaling Search of massive Biological data

GEMS

:: DESCRIPTION

GEMS is a suit of softweares for entropy-scaling searching of massive biological data.

Ammolite is production-quality software designed to do a Tanimoto distance similarity search over chemical graphs for small molecules.

MICA (Metagenomic Inquiry Compressive Acceleration) is a full drop-in replacement for BLASTX and DIAMOND supporting all command-line options that is 3.5x faster than DIAMOND (and over 3000x faster than BLASTX) with no loss in specificity and less than 5% loss in sensitivity.

esFragBag (entropy-scaling FragBag) is prototype software that applies entropy-scaling to accelerate only the all r-nearest neighbor search functionality of FragBag by a factor of ~10 with no loss in specificity and less than 0.2% loss in sensitivity.

::DEVELOPER

Berger Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

Ammolite, MICA, esFragBag

:: MORE INFORMATION

Citation

Entropy-scaling search of massive biological data.
Yu YW, Daniels NM, Danko DC, Berger B.
Cell Syst. 2015 Aug 26;1(2):130-140.

GEMS 1.5 – Biclustering Analysis of Expression data

GEMS 1.5

:: DESCRIPTION

GEMS (Gene Expression Mining Server) is a software for biclustering microarray data. Users may upload expression data and specify a set of criteria. GEMS then performs bicluster mining based on a Gibbs sampling paradigm. The web server provides a flexible and an useful platform for the discovery of co-expressed and potentially co-regulated gene modules

::DEVELOPER

Computational Genomics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ Windows / MacOsX
C++ Compiler

:: DOWNLOAD

GEMS

:: MORE INFORMATION

Citation:

GEMS: a web server for biclustering analysis of expression data.
Wu CJ, Kasif S.
Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W596-9.