Singularity wrapper for https://github.com/brielin/Popcorn (the version updated May 2022 based on Python3).
Brief getting started instructions, which should execute built-in example provided together with popcorn software:
singularity shell --home $PWD:/home containers/popcorn.sif
cp /tools/popcorn/test/* .
./test.bash
For EUR and EAS populations the reference files are included in reference folder.
Have a look here if you're new to git or Git LFS.
An easy start for making your own reference files would be to download 1kG data as processed in MAGMA:
wget https://ctg.cncr.nl/software/MAGMA/ref_data/g1000_eas.zip --no-check-certificate
wget https://ctg.cncr.nl/software/MAGMA/ref_data/g1000_afr.zip --no-check-certificate
wget https://ctg.cncr.nl/software/MAGMA/ref_data/g1000_eur.zip --no-check-certificate
To select individuals from 1kG sub-populations you may use the 1000GP_Phase3.sample file, as in the following example where we select ASW sub-population.
After that it's a good idea to exclude MHC region, and filter on MAF.
# ASW sub-population
cat 1000GP_Phase3.sample | grep ASW | awk '{print $1 " " $1}' > ASW.samples
plink3 --bfile g1000_afr --chr 6 --from-mb 25 --to-mb 35 --make-just-bim --out mhc_afr --threads 1
cat mhc_afr.bim | awk '{print $2}' > mhc_afr.justrs
plink --bfile g1000_afr --keep ASW.samples --exclude mhc_afr.justrs --maf 0.01 --make-bed --out g1000_asw_noMHC_maf0p01 # 61 individual
# EUR population
plink2 --bfile g1000_eur --chr 6 --from-mb 25 --to-mb 35 --make-just-bim --out mhc_eur --threads 1
cat mhc_eur.bim | awk '{print $2}' > mhc_eur.justrs
plink --bfile g1000_eur --exclude mhc_eur.justrs --maf 0.01 --make-bed --out g1000_eur_noMHC_maf0p01 # 503 individual
Once this is ready, once need to compute LD scores like this:
export POPCORN="singularity exec --home $PWD:/home popcorn/containers/popcorn.sif popcorn"
$POPCORN compute --SNPs_to_store 50000 --bfile refs/g1000_eur_noMHC_maf0p01 refs/g1000_eur.cscore
$POPCORN compute --SNPs_to_store 50000 --bfile refs/g1000_asw_noMHC_maf0p01 refs/g1000_asw.cscore
$POPCORN compute --SNPs_to_store 50000 --bfile1 refs/g1000_eur_noMHC_maf0p01 --bfile2 refs/g1000_asw_noMHC_maf0p01 refs/g1000_eur_asw.cscore
We assume you already have GWAS summary statistics, formatted according to POPCORN, i.e. with columns rsid a1 a2 Z N. Column names are case-sensitive, i.e. lowercase rsid, a1, a2, and capital case Z and N. The ACTG allele codes in a1 and a2 columns should be capital-case.
Finally, perform the analysis as follows:
# for the univariate analysis
$POPCORN fit --sfile data/TRAIT_EUR.sumstats --cfile refs/g1000_eur.cscore results/TRAIT_EUR.out
$POPCORN fit --sfile data/TRAIT_AAM.sumstats --cfile refs/g1000_asw.cscore results/TRAIT_AAM.out
# for the bivariate (cross-trait)
$POPCORN fit --sfile1 data/TRAIT_EUR.sumstats --sfile2 data/TRAIT_AAM.sumstats --cfile refs/g1000_eur_asw.cscore results/TRAIT_EUR_AAM.out
The resulting file will contain pgi measure, showing genetic impact correlation. See original software pages for futher details.
popcorn- Software for estimating correlation of trait effect sizes across populations
Below is the list of tools included in the different Dockerfile(s) and installer bash scripts for each container.
Please keep up to date (and update the main <popcorn>/README.md when pushing new container builds):
| container | OS/tool | version |
|---|---|---|
| popcorn.sif | ubuntu | 20.04 |
| popcorn.sif | python3 | python 3.10.6 |
| popcorn.sif | popcorn | https://github.com/ofrei/Popcorn @ fa1326c |
| (minor fix on top of the original https://github.com/brielin/Popcorn @ ef4455a) |
For instructions on how to build or rebuild containers using Docker and Singularity refer to <popcorn>/src/README.md.
If you face any issues, or if you need additional software, please let us know by creating a new issue.