orphan: |
---|
- Are your target genomes and the scoring file in compatible builds?
--min_overlap
defaults to 0.75 (75% of variants in scoring file must be present in target genomes). Try changing this parameter!
Did you forget to set --max_cpu
or --max_memory?
You can also edit nextflow.config
to configure cpu and memory permanently. nf-core
provides a set of example .config files, including examples for both institutional
compute clusters (e.g. Cambridge, Sanger) and cloud compute providers
(e.g. Google, AWS Tower and Batch). See :ref:`big job` for more information.
pgsc_calc
bundles dependencies using containers or conda. Did you remember
to specify -profile
? e.g. nextflow run pgscatalog/pgsc_calc -profile
docker,test
Multiple profiles can be combined with a comma. The test profile is used only for checking the pipeline is installed and working correctly.
If you use a "chr" prefix in the chromosome column of your VCF, please remove it. Here's a simple method to do this (thanks to Rvtests):
(zgrep ^"#" $your_old_vcf; zgrep -v ^"#" $your_old_vcf | sed 's:^chr::ig' | sort -k1,1n -k2,2n) | bgzip -c > $your_vcf_file.gz
VCF file(s) containing variants on non-standard chromsomes or patches (e.g. chr1_gl000191_random) will also currently fail our pipeline as it only takes human chromosomes as input (1-22, X, Y, XY). One way to remove these variants is to download and run plink2 and convert your data to plink files that can be used with the calculator using the following command:
plink2 --vcf [yourfile] --allow-extra-chr --chr 1-22, X, Y, XY -make-pgen --out [yourfile]_axy
however other methods to filter these variants from VCFs also exist.
By default the pipeline uses the genotypes present in the GT
field of the VCF file. If you would like
to use imputed dosages you must add a vcf_genotype_field
field column to the samplesheet with the DS
value.
See :ref:`setup samplesheet` for more information.