GREGOR

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GREGOR

GREGOR (Genomic Regulatory Elements and Gwas Overlap algoRithm) is a tool built to evaluate global enrichment of trait-associated variants in experimentally annotated epigenomic regulatory features.

Because all reference data are version hg19, please make sure that your index SNP list and BED files are also version hg19.

Get GREGOR Source Codes

Download from webpage

Through this link GREGOR, you can download a copy of GREGOR.

Build GREGOR

To build GREGOR, copy the GREGOR package to the directory you want, and then run the following command:

 tar xzvf GREGOR.tar.gz

After you unzip, you can find 3 directories in "GREGOR" (./example ./lib ./script).

Download reference files

Download the reference files from this link GREGOR Download, then un-package the file

 tar xzvf GREGOR.ref.tar.gz

After unzip, you will get 47 reference files in the directory "~/ref"

Basic Usage Example

When you run

 perl GREGOR.pl

you will get some information about GREGOR


GREGOR.pl : Functional annotation of trait-associated variants


This program tests for enrichment of an input list of trait-associated index SNPs ([chr:pos] format or rsID, hg19) in experimentally annotated regulatory domains (BED files).

Note: the index SNPs should be hg19 version. All maf and LD data are from 1000G EUR samples! (Release date : May 21, 2011)

Version : 1.1.0

Report Bug(s) : jich[at]umich[dot]edu


Usage : perl GREGOR.pl --conf [conf.file]



The following command is a typical command line:

 perl GREGOR.pl --conf [conf.file]

Example configuration file can be found in example directory. Users have to modify the configurations before running.

Configuration File

The example configuration file below illustrate how to configure the GREGOR configuration file.

 ###############################################################################
 # CHIPSEQ ENRICHMENT CONFIGURATION FILE
 # This configuration file contains run-time configuration of
 # CHIP_SEQ ENRICHMENT
 ###############################################################################
 ## KEY ELEMENTS TO CONFIGURE : NEED TO MODIFY
 ###############################################################################
 INDEX_SNP_FILE = /workingdirectory/example/example.index.snps.rsid.list.txt    ## e.g. /workingdirectory/example/example.index.snps.rsid.list.txt
 BED_FILE_INDEX = /workingdirectory/example/example.bed.file.index ## e.g. /workingdirectory/example/example.bed.file.index
 REF_DIR = /workingdirectory/ref/ ## reference directory
 R2THRESHOLD = 0.7
 LDWINDOWSIZE = 1000000
 OUT_DIR = /workingdirectory/example/example.rsid.20130808/ ## e.g. /workingdirectory/example/example.rsid.20130808/
 MIN_NEIGHBOR_NUM = 500
 BEDFILE_IS_SORTED = True
 BATCHTYPE = slurm
 BATCHOPTS = --partition=main --time=0:30:0

In the config file, there are several parameters to adjust:

INDEX_SNP_FILE: This file contains a single column of trait-associated input SNPs, without a header. Variants can be listed in rsid or hg19 chr:pos format.

BED_FILE_INDEX: This file lists the datasets (e.g. BED files) to be used for enrichment analysis. Use complete paths to file locations and make sure positions are in hg19 format.

REF_DIR: Define reference file directory which you download at here.

R2THRESHOLD and LDWINDOWSIZE: These two parameters define the index SNP (and control SNP) LD proxies by r2 threshold and LD window size.

OUT_DIR: All result files are saved to this folder, where the script will create multiple sub-directories. Index SNPs are in the folder "index_SNP"; Random SNPs are in the folder "random_SNP".

MIN_NEIGHBOR_NUM: Define the minimum number of control SNPs for each index SNP. Script will find no less than this number around every index SNP. If you make this number of control SNPs very large, the control SNPs will be less closely matched on the three matching properties (distance to nearest gene, frequency and number of SNPs in LD).

BEDFILE_IS_SORTED: True or false, depending on whether the BED files listed in the index file are sorted.

BATCHTYPE: We have three options for this parameter. When you run GREGOR on local machine, specify "local"; when run on MOSIX system, specify "mosix"; when run on SLURM system, specify "slurm".

BATCHOPTS: This parameter works with BATCHTYPE when you specify "mosix" or "slurm". For example, when you define mosix, this parameter can be "-E/tmp -i -m2000 -j10,11,12,13,14,15,16 sh -c"; when you define "slurm", it can be "--partition=1000g --time=0:30:0"

Results Output

The file StatisticSummaryFile.txt in the output directory contains enrichment results with the following information:

GREGOR Summary 20160201.png

Bed_File: The individual datasets used in the enrichment analysis

InBed_Index_SNP: Number of index SNPs or their LD proxies that overlaps regulatory regions in each dataset

Pvalue: P-value calculated assuming a sum of binomial distributions to represent the number of index SNPs (or LD proxies) that overlap a dataset compared to the expectation observed in the matched control sets

  • Note:
    • SNPs that cannot be converted from rsID to chr:pos format are listed in the output file rsid.index.snp.txt. SNPs for which there are no LD proxies or no MAF data available are listed in the output file nonannoted.index.snp.txt.
    • If one index SNP and its LD-buddies are not in any bed region, the Pvalue could be defined to "NA"

Testing GREGOR

There is an example directory in ~/GREGOR. You can find index SNP file, 3 bed files, bed file index and example config file. After change your config file, you can run a test.

 perl ~/GREGOR/script/GREGOR.pl --conf ~/GREGOR/example/example.conf

After running 2 minutes +/- 1 minutes. You will get result file "StatisticSummaryFile.txt" in your defined output directory.

Acknowledgements

GREGOR is the result of collaborative efforts by Cristen Willer, Jin Chen, Wei Zhou, Ellen Schmidt, He Zhang, and Goncalo Abecasis. Please email Cristen Willer [cristen@umich.edu] with any questions.