BIMBAM 1.0 – Bayesian IMputation-Based Association Mapping

BIMBAM 1.0

:: DESCRIPTION

BIMBAM (Bayesian IMputation-Based Association Mapping)implements methods for assocation mapping. BIMBAM can handle both large association studies (e.g., genome scans) and smaller studies of candidate genes/regions.

::DEVELOPER

Yongtao Guan

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac

:: DOWNLOAD

BIMBAM

:: MORE INFORMATION

Citation

PLoS Genet. 2008 Dec;4(12):e1000279. doi: 10.1371/journal.pgen.1000279. Epub 2008 Dec 5.
Practical issues in imputation-based association mapping.
Guan Y1, Stephens M.

Servin, B and Stephens, M (2007).
Imputation-based analysis of association studies: candidate genes and quantitative traits.
PLoS Genet. 2007 Jul;3(7):e114. Epub 2007 May 30.

LMM-Lasso – Lasso Multi-Marker Mixed Model for Association Mapping with Population Structure Correction

LMM-Lasso

:: DESCRIPTION

LMM-Lasso is a linear mixed models that allows for both multi-locus mapping and correction for confounding effects.

::DEVELOPER

Machine Learning and Computational Biology Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Python

:: DOWNLOAD

 LMM-Lasso

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Jan 15;29(2):206-14. doi: 10.1093/bioinformatics/bts669.
A Lasso multi-marker mixed model for association mapping with population structure correction.
Rakitsch B, Lippert C, Stegle O, Borgwardt K.

GLASCOW – Haplotype-based Association Mapping for Binary Traits in Structured Populations

GLASCOW

:: DESCRIPTION

GLASCOW performs genome-wide association studies using Generalized Linear Mixed Models (GLMM) and a score test as described in Zhang et al. Association is performed between factors (SNPs or haplotypes) and a phenotype (with different type of distributions:normal, binomial, counts). The method relies on two steps. In the first one, a GLMM without the factor of interest is solved (including estimation of variance components and of fixed and random effects solutions) and residuals are computed. In the second step, the residuals are used to test significance of association between the factor and the phenotype at each position along the genome (or the selected data).

::DEVELOPER

Unit of Animal Genomics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 GLASCOW

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Oct 1;28(19):2467-73. Epub 2012 Jun 17.
Ancestral haplotype-based association mapping with generalized linear mixed models accounting for stratification.
Zhang Z, Guillaume F, Sartelet A, Charlier C, Georges M, Farnir F, Druet T.

FastMap 2.0 – Fast Association Mapping in Heterozygous Populations

FastMap 2.0

:: DESCRIPTION

FastMap is a software for fast and efficient eQTL mapping in homozygous inbred populations with binary allele calls. FastMap exploits the discrete nature and structure of the measured single nucleotide polymorphisms (SNPs). In particular, SNPs are organized into a Hamming distance-based tree that minimizes the number of arithmetic operations required to calculate the association of a SNP by making use of the association of its parent SNP in the tree. FastMap’s tree can be used to perform both single marker mapping and haplotype association mapping over an m-SNP window. These performance enhancements also permit permutation-based significance testing.

::DEVELOPER

Carolina Center for Computational Toxicology

:: SCREENSHOTS

::REQUIREMENTS

  • Linux/Windows/MacOsX
  • Java

:: DOWNLOAD

 FastMap

:: MORE INFORMATION

Citation

D.M. Gatti, A.A. Shabalin, T.C. Lam, F.A. Wright, I. Rusyn, and A.B. Nobel.
FastMap: Fast eQTL mapping in homozygous populations.
Bioinformatics, 25(4):482, 2009.

BEAMimpute – Bayesian Epistatis Association Mapping via Imputation

BEAMimpute

:: DESCRIPTION

BEAMimpute (Bayesian Epistatis Association Mapping via Imputation)  uses Markov Chain Monte Carlo (MCMC) to impute untyped SNPs and detect both single-marker and interaction effects from the imputed case-control SNP data.

::DEVELOPER

Yu Zhang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 BEAMimpute

:: MORE INFORMATION

Citation

Nat Genet. 2007 Sep;39(9):1167-73. Epub 2007 Aug 26.
Bayesian inference of epistatic interactions in case-control studies.
Zhang Y, Liu JS.

BEAM 3 – Disease Association Mapping

BEAM 3

:: DESCRIPTION

BEAM (Bayesian Epistasis Association Mapping) is a software for SNP-SNP interaction association mapping based on graph models, infers disease-SNP graph and automatically accounts for linkage disequilibrium.

::DEVELOPER

Yu Zhang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 BEAM

:: MORE INFORMATION

Citation

Nat Genet. 2007 Sep;39(9):1167-73. Epub 2007 Aug 26.
Bayesian inference of epistatic interactions in case-control studies.
Zhang Y, Liu JS.

CAMP – Coalescent based Association Mapping

CAMP

:: DESCRIPTION

CAMP (Coalescent based Association MaPping) is a tool for association studies.It takes into account the trade-off between the complexity of the genealogy and the power lost due to the additional multiple hypotheses.

::DEVELOPER

Gad Kimmel

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

CAMP

:: MORE INFORMATION

Citation

Gad Kimmel et al.
Association Mapping and Significance Estimation via the Coalescent
Am J Hum Genet. 2008 December 12; 83(6): 675–683.

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.

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