Difference between revisions of "GREGOR"

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Download the reference files from this link [http://www.sph.umich.edu/csg/jich/FallInBed/  FallInBed Download],then un-package the file
 
Download the reference files from this link [http://www.sph.umich.edu/csg/jich/FallInBed/  FallInBed Download],then un-package the file
  
   tar xzvf FallInBed.reference.tar.gz
+
   tar xzvf FallInBed.ref.tar.gz
  
 
After unzip, copy all reference files to directory "./ref"
 
After unzip, copy all reference files to directory "./ref"

Revision as of 16:23, 9 August 2013

FallInBed

FallInBed is a tool to test for enrichment of an input list of trait-associated index SNPs in experimentally annotated regulatory domains (BED files). Because all reference data are hg19, so your index SNP and bed files should also be hg19 version.

Download FallInBed

Through this this link FallInBed Download, you can download a copy of FallInBed.

Build FallInBed

To build FallInBed, copy the FallInBed package to the directory your want, and then run the following command.

 tar xzvf FallInBed.tar.gz

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

Download reference files

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

 tar xzvf FallInBed.ref.tar.gz

After unzip, copy all reference files to directory "./ref"

Basic Usage Example

When you run

 perl FallInBed.pl

you will get some information about FallInBed


FallInBeds.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 FallInBeds.pl --conf [conf.file]



The following command is a typical command line:

 perl FallInBed.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 FallInBed 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 = /net/dumbo/home/jchen/prj/chiseq/codes/FallInBed_Binomial/example/example.index.snps.rsid.list.txt    ## e.g. /home/myid/data/FallInBed/example.snp.txt
 BED_FILE_INDEX = /net/dumbo/home/jchen/prj/chiseq/codes/FallInBed_Binomial/example/example.bed.file.index ## e.g. /home/myid/data/FallInBed/bedfiles.index
 R2THRESHOLD = 0.7
 LDWINDOWSIZE = 1000000
 OUT_DIR = /net/dumbo/home/jchen/prj/chiseq/codes/FallInBed_Binomial/example/example.rsid.20130808/ ## e.g. /home/myid/data/FallInBed/result/
 MIN_NEIGHBOR_NUM = 500
 BEDFILE_IS_SORTED = true
 MOSRUN = mosbatch -E/tmp -i -m2000 -j20,43,122,135,137,138,149,151,153,154,155,156,162,163 sh -c


In configure file, there are 10 parameters.

INDEX_SNP_FILE: define the index SNP file. In this file, there is only one column without header. Index SNP can be rsid or chr/pos format.

BED_FILE_INDEX: define the bed files.

R2THRESHOLD and LDWINDOWSIZE: these two parameters are defined the LD buddy.

RANDOM_LIST_NUM: define how many random lists, e.g. 100 or 1000

OUT_DIR: All result files are saved to this folder. In this folder, script will create multi-subdirectories. Index SNPs are in the folder "index_SNP"; Random SNPs are in the folder "random_SNP".

MIN_NEIGHBOR_NUM: define neighbor number around index SNP. Script will find no less than this number around every index SNP.

Acknowledgements

FallInBed is a result from collaborative effort by Cristen Willer, Jin Chen, Wei Zhou, Ellen Marie Schmidt, He Zhang, and Goncalo Abecasis. Please email to Cristen Willer [cristen@umich.edu ] for any questions.