Update Mouse Genome

#Overview of steps

Update Jax Imputed Database SNP Locations

• Jax markers can be found here [http://cgd.jax.org/datasets/popgen/imputed.shtml Center for Genome Dynamics]
• Limiting Jax Markers.R imports data and limits SNPs based on confidence and information

Update Sanger Institute C57BL/6J and DBA/2J SNP locations

• Here is the link to their latest version of SNPs [ftp://ftp-mouse.sanger.ac.uk/current_snps/ Mouse Genome Project]
• I haven't dealt with their new format of SNPs

Update locations of BXD SNPs from the Wellcome Trust-CTC (for PhenoGen and eQTL - not mask)

• Data for the mm37 build can be download from here [http://gscan.well.ox.ac.uk/gsBleadingEdge/mouse.snp.selector.cgi Mouse SNP Selector]

Update Mouse Exon and 430 version 2 SNP Masks

• Download sequence information for the UCSC genome browser. It is easiest to download combined file.
• Download probe sequence information from Affymetrix
• Download and install BLAT
• Align probes to new genome
• Update masks
  • Identify probes that hit the genome once and only once (findPerfectMatches.R)
  • Use BEDtools to find overlap between SNPs and probes (intersectSNPsAndPerfectMatchedProbes.txt)
  • Reformat original PGF file (read in pgf file.txt)
  • Eliminate probes from temporary PGF file (Eliminate.Probes.R)
  • Create new PS files (Eliminate.Probes.R)
  • Create new MPS files (Eliminate.Probes.R, updatingFullTransFile.R, and creating new *.mps file.txt)
  • Reformat new PGF file (creating new PGF file.txt)>>
• Normalize Rat Exon Array data using new mask
• Calculate heritability
• Calculate eQTL with genome-wide pvalues
• Calculate eQTL with locus-specific pvalues
• Generate LOD plots

#Current Method Aug 2013

1. Run blat
   ./blat -stepSize=5 -minScore=20 -minIdentity=1 -repMatch=2253 /Volumes/Data/mm10/index/mm10.fa RaEx-1_0-st-v1.probe.fa blatOutput.psl
   Note: It may seem like you can increase the minScore and minIdentity but this can cause blat to miss perfect matches. So leave it alone and filter the .psl file with the R script or some other method.

2. Identify probes that hit the genome once and only once (findPerfectMatches_Exon.R - Exon array or findPerfectMatches_3Prime.R)

   • Modified by only doing the probe location output as a bed file. Skip combining SNPS to allow for different combinations of SNPs to be used for masking.

3. Create BED files for SNPs for each strain. (Currently only ILS/ISS which were separate already)

   • Converted from VCF using bedops(vcf2bed). Complete files not the unique SNPs (ILS_VQSR_BOTH_homozygousVariants.vcf and ISS_VQSR_BOTH_homozygousVariants.vcf)

4. Find intersection of Probe bed and SNP bed for each strain.

   • Use BEDtools to find overlap between SNPs and probes (intersectSNPsAndPerfectMatchedProbes.txt)
     ./intersectBed -a /Volumes/Data/mm10/array/MoEx/Aligned/MoEx1_0st_probe.default.perfectMatches.wStrand.txt -b /Volumes/Data/mm10/snps/sanger/snps_DBA.bed -c > /Volumes/Data/mm10/array/MoEx/SNPs_Probes/DBA_snpsInProbes.txt

5. Combine SNPs and Probes and perform filtering and output Masks (Exon arrays)
   perl CreateMaskExon.pl /Volumes/Data/mm10/array/MoEx MoEx-1_0-st-v1.r2.pgf DBA MoEx-1_0-st-v1.r2.dt1.mm9. MoEx-1_0-st-v1.r2.DBA.MASKED.perl.pgf mm10 MASKED.perl MoEx-1_0-st-v1.r2.dt1.mm9.csv

   • Arguments are:
     • Path to folder for the array type(Ex. MoEx)
     • PGF file name
     • Comma separated list of strain snps to include(just strain name prefix of file Strain_snpsInProbes.txt) Strain,Strain2,Strain3
     • Prefix including last . up to core, extended etc for the source files.(Downloaded from affy)
     • Output pgf file name
     • version of genome ex mm9,mm10
     • label to append to all files output(this can be anything avoid spaces)
     • The csv file linking Transcript clusters and probe sets(Downloaded from affy)

Update mouse genome details