NAME

       GWAMA - Genome-Wide Association Meta Analysis

SYNOPSIS

       GWAMA [options]

DESCRIPTION

       GWAMA  (Genome-Wide  Association  Meta  Analysis)  software  performs meta-analysis of the
       results of GWA studies of binary or  quantitative  phenotypes.  Fixed-  and  random-effect
       meta-analyses  are  performed for both directly genotyped and imputed SNPs using estimates
       of the allelic odds ratio and 95% confidence interval for binary traits, and estimates  of
       the  allelic effect size and standard error for quantitative phenotypes. GWAMA can be used
       for analysing the results of  all  different  genetic  models  (multiplicative,  additive,
       dominant,  recessive).  The  software  incorporates  error trapping facilities to identify
       strand alignment errors and allele  flipping,  and  performs  tests  of  heterogeneity  of
       effects between studies.

OPTIONS

       -i, --filelist=filename
              Specify studies' result files. Default = gwama.in

       -o, --output=fileroot
              Specify file root for output of analysis. Default = gwama (gwama.out, gwama.gc.out)

       -r, --random
              Use random effect correction. Default = disabled

       -gc, --genomic_control
              Use genomic control for adjusting studies' result files. Default = disabled

       -gco, --genomic_control_output
              Use  genomic  control  on meta-analysis summary (i.e. results of meta- analysis are
              corrected for gc). Default = disabled

       -qt, --quantitative
              Select quantitative trait version (BETA and SE columns). Default = binary trait

       -m, --map=filename
              Select file name for marker map.

       -t, --threshold=0-1
              The p-value threshold for showing direction in summary effect directions. Default =
              1

       --no_alleles
              No allele information has been given. Expecting always the same EA.

       --indel_alleles
              Allele labes might contain more than single letter. No strand checks.

       --sex  Run  gender-differentiated  and gender- heterogeneity analysis (method described in
              paper Magi, Lindgren & Morris 2010). Gender info must be provided in filelist file.
              (second column after file names is either M or F).

       --filter
              Set a filtering based on column header. It needs 3 arguments: column name, equation
              [>,<,>=,<=,==,!=], filter value. Multiple filters can be set.

       --name_marker
              Alternative header to marker name col.

       --name_strand
              Alternative header to strand column.

       --name_n
              Alternative header to sample size col.

       --name_ea
              Alternative header to effect allele column.

       --name_nea
              Alternative header to non-effect allele column.

       --name_eaf
              Alternative header to effect allele frequency column.

       --name_beta
              Alternative header to beta column.

       --name_se
              Alternative header to std. err. col.

       --name_or
              Alternative header to OR column.

       --name_or_95l
              Alternative header to OR 95L column.

       --name_or_95u
              Alternative header to OR 95U column.

       -h, --help
              Print this help.

       -v, --version
              Print GWAMA version number.  This manual page must be insufficient. Please use  the
              help  option  for a quick reminder of the options of gwama or turn to its home page
              with the online documentation or the downloadable manual.

SEE ALSO

       http://www.geenivaramu.ee/en/tools/gwama

AUTHOR

       GWAMA was written by Reedik Magi and Andrew P Morris.