GPASS 1.0 – Genome-wide Poisson Approximation for Statistical Significance

GPASS 1.0

:: DESCRIPTION

GPASS (Genome-wide Poisson Approximation for Statistical Significance) detects SNP disease associations in case control studies, controls FWER and FDR adjusting for dependence/linkage disequilibrium.

::DEVELOPER

Yu Zhang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 GPASS

:: MORE INFORMATION

ALOHA 1.2 – Genome-wide Analysis of Allele Frequency

ALOHA 1.2

:: DESCRIPTION

ALOHA (Allele-Frequency/Loss-of-Heterozygosity/Allelic-Imbalance) is a tool for a genome-wide analysis of allele frequency, detection of loss of heterozygosity and identification of allelic imbalance. Moreover, chromosome-wise allele frequency biplots are provided for sample classification, outlier detection and SNP clustering.

::DEVELOPER

Hsin-Chou Yang

:: SCREENSHOTS

::REQUIREMENTS

:: DOWNLOAD

 ALOHA

:: MORE INFORMATION

Citation

Hsin-Chou Yang*, Hsin-Chi Lin, Mei-Chu Huang, Ling-Hui Li, Wen-Harn Pan, Jer-Yuarn Wu, and Yuan-Tsong Chen (2010).
A new analysis tool for individual-level allele frequency for genomic studies.
BMC Genomics 11: 415

KBAT 1.2 – Genome-wide and Candiate-region Association Mapping

KBAT 1.2

:: DESCRIPTION

KBAT (Kemel- Based Association Test) is a convenient analysis tool for genome-wide and candiate-region association mapping.

::DEVELOPER

Hsin-Chou Yang, Hsin-Yi Hsieh and Cathy SJ Fann(Institute of Biomedical Sciences, Academia Sinica, Taiwan)

:: SCREENSHOTS

::REQUIREMENTS

:: DOWNLOAD

 KBAT

:: MORE INFORMATION

Citation

Hsin-Chou Yang, Hsin-Yi Hsieh & Cathy SJ Fann. (2008)
Kernel-based association test.
Genetics 179, 1057-1068.

HPeak 2.1 – Define Genome-wide ChIP-enriched Peaks in Human Genome

HPeak 2.1

:: DESCRIPTION

HPeak is a hidden Markov model-based approach that can accurately pinpoint regions to where significantly more sequence reads map. Testing on real data shows that these regions are indeed highly enriched by the right protein binding sites.ChIP-Seq is an important application of the massively parallel sequencing technologies aiming to identify all the locations in the genome where a specific protein binds. While direct counting of the sequencing reads can reveal many such binding sites, it is desirable to develop a statistical sound method to explicitly model the uncertainties involved for better and more interpretable results.

::DEVELOPER

Steve Qin @ the Center for Statistical Genetics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows

:: DOWNLOAD

  HPeak

:: MORE INFORMATION

Citation

Qin ZS, Yu J, Shen J, Maher CA, Hu M, Kalyana-Sundaram S, Yu J, Chinnaiyan AM (2010).
HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data.
BMC Bioinformatics, 11:369

Exit mobile version