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Copyright
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Copyright (c) 2015, Hailiang Huang and Mark J Daly, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston MA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

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   list of conditions and the following disclaimer.
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Synopsis
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A Fine-mapping method using flat prior with steepest descent approximation.  Method details available at: HTTP://biorxiv.org/content/early/2015/10/20/028688

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Prerequisites
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The R nnet package is required for this method.

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Usage
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A sample dataset was provided at "dat/", including:
1. example.raw: genotype data generated using the --recodeA option in PLINK (HTTP://pngu.mgh.harvard.edu/~purcell/plink/).  Each row is a sample and each column is a SNP.
2. example.pheno: phenotype for the samples. 0 is control, 1 is UC and 2 is CD.
3. pcs.txt: covariate file. Each row is a sample and each column is a covariate you want to adjust for. 

Fine-mapping can be performed by calling source("code/finemapping.r") in the R console. Output files will be saved in the "result/" folder, including:
1. repos.txt: summary statistics of all SNPs (mostly for diagnostics).
2. credible.txt: a list of SNPs in the 99% credible set. Column headers should be self-explanatory.  The "probNormed" column has the posterior probability for the SNPs, and the "R" column is the correlation coefficient between the SNP and the lead SNP in the signal.