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Training

In the two toy-data examples the target population was African (AFR) and the base population was European (EUR). In these examples each population had a corresponding:

  • LD reference panel
  • GWAS summary statistics file
  • Individual levels genotype data in plink binary format
  • Phenotype data

Here we consider using BridgePRS in other scenarios with less available data. In each of these examples the task is to create valid configuration files given the described scenario.

Challenge 1:

I have access to genotype/phenotype data (<1000 samples, continuous phenotype) from a population in Central Africa (1,2). I would like ot run PRS as accurately as possible, but my dataset is not large enough to conduct GWAS, however, I do have access to a moderately sized (25,000 samples) GWAS summary statistics from a West African population (3) and access to summary statistics from a GWAS of a large (500k) European population (4). I also have access to the 1000G reference panels, how can I analyze my data?

Available Data:

  1. caf/genotypes/caf_genotype.bed, caf_genotype.bim, caf_genotype.fam
  2. caf/phenotypes/caf_test.dat, ukb/phenotypes/caf_validation.dat
  3. yoruba/sumstats/yoruba.chr1.glm.gz,...,yoruba.chr22.glm.gz
  4. ukb/sumstats/ukb.sumstats.gz
  5. 1000G Reference Panel

Can you fill out the configuration files to carry this out? 

POP=
LDPOP=
LD_PATH=
SUMSTATS_PREFIX=
SUMSTATS_SUFFIX=
SUMSTATS_SIZE=
GENOTYPE_PREFIX=
PHENOTYPE_FILE=
VALIDATION_FILE=

POP=CAF
LDPOP=AFR 
LD_PATH=data/1000G_SAMPLE
SUMSTATS_PREFIX=yoruba/sumstats/yoruba.chr 
SUMSTATS_SUFFIX=.glm.gz 
SUMSTATS_SIZE=25000
GENOTYPE_PREFIX=caf/genotypes/caf_genotype 
PHENOTYPE_FILE=caf/phenotypes/caf_test.dat  
VALIDATION_FILE=caf/phenotypes/caf_validation.dat 

POP=
LDPOP=
LDPATH= 
SUMSTATS_FILE=
SUMSTATS_SUFFIX=
SUMSTATS_SIZE=
GENOTYPE_PREFIX=
PHENOTYPE_FILES=

POP=EUR
LDPOP=EUR
LD_PATH=data/1000G_SAMPLE
SUMSTATS_FILE=ukb/sumstats/ukb.sumstats.gz 
SUMSTATS_SIZE=500000
GENOTYPE_PREFIX=caf/genotypes/caf_genotype 
PHENOTYPE_FILE=caf/phenotypes/caf_test.dat  
VALIDATION_FILE=caf/phenotypes/caf_validation.dat

Challenge 2:

I have access to GWAS summary statistics (1) and genotype/phenotype (2,3) data (>2000 samples, binary phenotype) from a moderate sized population in Eastern Europe. I have reason to believe that this population has unique LD structure and would like to incorporate this into my model. I also have GWAS (4) and genotype/phenotype data from the UKB biobank (5,6) that I wish to use to improve my results, how should I do this?

  1. ukr/sumstats/ukr.sumstats.out
  2. ukr/genotypes/chr1.bed,bim,fam...chr22.bed,bin,fam,
  3. ukr/phenotypes/ukr_test.dat, ukr/phenotypes/ukr_validation.dat
  4. ukb/sumstats/ukb.sumstats.gz
  5. ukb/genotypes/chr1.bed,bim,fam...chr22.bed,bin,fam
  6. ukb/phenotypes/ukb_test.dat, ukb/phenotypes/ukb_validation.dat 
POP=
LDPOP=
LDPATH=
SUMSTATS_PREFIX=
GENOTYPE_PREFIX=
PHENOTYPE_FILE=
VALIDATION_FILE=

POP=ukr
LDPOP=ukr*
LDPATH=CUSTOM
SUMSTATS_PREFIX=ukr/sumstats/ukr.sumstats  
SUMSTATS_SIZE=2000 
GENOTYPE_PREFIX=ukr/phenotypes/chr
PHENOTYPE_FILE=ukr/phenotypes/ukr_test.dat 
VALIDATION_FILE=ukr/phenotypes/ukr_validation.dat

POP=
LDPOP=
SUMSTATS_PREFIX=
GENOTYPE_PREFIX=
PHENOTYPE_FILE=
VALIDATION_FILE=

POP=UKB
LDPOP=EUR 
LDPATH=1000G
SUMSTATS_PREFIX=ukb/sumstats/ukb.sumstats
SUMSTATS_SIZE=500000
GENOTYPE_PREFIX=ukb/genotypes/chr
PHENOTYPE_FILE=ukb/phenotypes/ukb_test.dat 
VALIDATION_FILE=ukb/phenotypes/ukb_validation.dat