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fGWAS: Functional GWAS software (Version 1.0)



Description:

The fGWAS (Function Genome-wide association study) is a new concept to evaluate additive and dominant effect for every SNP and identify the significant SNPs from huge SNP data. Since R. Wu[1] et al. put forward this new concept, 3 statistical models have been developed to find the relationship between SNP data and the longitudinal traits, including Bayesian Lasso[2], Bayesian Group Lasso[3] and dynamic model[4].

The fGWAS software aims at building a general platform to analyse SNP data with longitudinal trails. This platform provides multiple statistical models and uniform interface to the end-users. We develop this software in C/C++ to gain fast speed and more compatibility with main computing platform. The details will be described in the section 5 and in the introduction document.

So far the fGWAS software implements one statistical model, the Glasso model, the rest of the models will be released soon.

Here we refer to the following publications for the theoretical foundation of this software. If you appreciate this software then please cite the following papers in your work.

[1] Jiangtao Luo, Arthur Berg, Kwangi Ahn, Kiranmoy Das, Jiahan Li, Zhong Wang, Yao Li, Rongling Wu. Functional genome-wide association studies of longitudinal traits. In: Handbook of Adaptive Designs in Pharmaceutical and Clinical Development 2010, edited by S. C. Chow. Wiley, London, UK.
[2] Jiahan Li, Kiranmoy Das, Guifang fu, Runze Li and Rongling Wu. The Bayesian Lasso for Genome-wide Associations Studies. Bioinformatics 2010. DOI:10.1093/bioinformatics/btq688
[3] Jiahan Li, Runze Li, and Rongling Wu. Bayesian Group LASSO for Varying-Coefficient Models With Application to Functional Genome-Wide Association Studies.
[4] Kiranmoy Das, Jiahan Li, Zhong Wang, Chunfa Tong, Guifang Fu, Yao Li, Meng Xu, Kwangmi Ahn, David Mauger, Runze Li, Rongling Wu. A dynamic model for functional genome-wide association studies. Human Genetics, 2011. DOI:10.1007/s00439-011-0960-6

Download:

The software for Windows OS is available now. We are planning to release the versions for the LINUX and Mac. The document also can be downloaded by the following link.


Installation:

It is easy to install this software in the Windows, just download the setup file and run it.

Architecture:

Generally the fGWAS software integrates two types of program, GUI program and model program. The following figure gives some details about the architecture.

The GUI program displays a friendly user interface which implements project management, task management and data visualization. The end-users create a data analysis project by selecting phenotype file and multiple genotype files. Because so far just one model is integrated into this system, the users don't need to select a model to fit the data. If the projects are ready to run, the end-users can decide how many tasks can be performed in parallel according to the CPU's count. During the tasks’ execution, the GUI program will detect their status and show their progress to the end-users. After the tasks are completed, the GUI program can show and export the results.

For more details of the GUI program, please click HERE

The model programs implement the details of the algorithms which can analyze the relationship between phenotypic data and genotypic data. In order to obtain high speed, we do it in C/C++ language based on our frame work and the R library. So our model programs can be run in the operating systems which the R can run. The model programs can be executed in two ways. It is simple to run them under the GUI program. The GUI program feeds these models the parameters and asks them outputting the status while their running. After the model's execution is completed successfully, the GUI program can show the results to the end-users. Another way to run the model programs is command line. The end-users have to understand the parameters and do some configuration files in advance.

For more details of the Glasso program, please click HERE

Update History:

03/03/2011: Version 1.0 is released.


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