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                                         Alabama Genomics Health Initiative (AGHIpop)
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Analytical pipeline to analyze data from the Alabama Genomic Health Initiative population based cohort.A tool for performing
Genome-Wide Association Study (GWAS) analysis.

This pipeline uses PLINK open-source whole genome association analysis toolset, designed to perform a range of basic,large-scale analyses in a computationally efficient manner.

Association Analysis is run on both the raw genotype and the imputed data.

GWAS summary report is generated with the following results included.

        1. Manhattan plots
        2. Q-Q plots
        3. Tables for top 10 or significant variants and closed genes
        4. LocusZoom plot for the variant with lowest P value
        5. Table for Meta-analysis
        6. Table for top 10 or significant genes from gene-based analysis
        7. Resulted gene-set analysis

#Getting Started
     ## copy copy_me directory to the location you want to run GWAS
     ## You need to fill GWAS.config file with the required details based on the number of study and population
     ## You need to create a directory where you want to launch the pipeline and mention its path in the config file
     ## You need to place all your study specific phenotype files in the above created path

#Prerequisites
##PLINK software and version:
     PLINK open-source whole genome association analysis toolset, designed to perform a range of basic,large-scale analyses
     in a computationally efficient manner.

## R version and libraries:
    This pipeline was adapted for module R/3.3.1-foss-2016b on the UAB Cheaha. All dependent R libraries have
    been installed and their paths .libPaths("/data/project/ubrite/pipelines/AGHIpop/softwares/R_3.3.1_packages")

#Running the Analysis
## Sample usage:
      Working Directory: "/data/project/ubrite/pipelines/AGHIpop/example" and the results will be saved to: "/data/project/ubrite/pipelines/AGHIpop/example/dummy/myWD" and "/data/project/ubrite/pipelines/AGHIpop/example/dummy/myRT"

## copy the following code to launch the pipeline:
        sbatch /data/project/ubrite/pipelines/AGHIpop/GWAS_Pip/GWAS_Pipeline_main_V2.job GWAS.config

## Job status can be checked using the following command
      squeue -u [user-id] #blazer ID

## Result data files:
        1. Resulted data files will be stored at the result directory for producing tables and figures in the report.
        The report file "Pipeline_PredmGWAS_[trait_name].html" is always located at the working directory instead.
        2. The result subdirectory "chr1~22" are used to store gene-based analysis results chromosome by chromosome and
        subdirectory "allchrs" is used for gene-based analysis for all 22 chromosomes and gene-set analysis

## Common usage errors:
        1. This pipeine was written based on R/3.3.1-foss-2016b, please be careful of any updating of R version

## Study data requirement:
        *  phenotype data: phenotype file should have the required columns in the below format
           FID IID TRAIT CO-VARIATE1 CO-VARIATE2 CO-VARIATE3 ...
        *  TRAIT column should always be the third column follwing by co-variates
        *  In addition, only 22 autosomal chromosomes are chosen for analysis

## System issue:
          So far only R/3.3.1-foss-2016b module on the cheaha server has be equipped with most libraries such as 'knitr'
        'rmarkdown' and comprehensive graph supports.