Comments (1)
@jjfarrell it could be possible to do this with the Glow Pipe Transformer
for example if you joined the variants to the --interaction-snp-file
, partitioned on the set of interacting SNPs you want to test and then fed the resulting dataframe through the pipe transformer, running regenie on the command line for each partition
@henrydavidge what do you think?
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Related Issues (20)
- Improve docs: Document usage of schema when reading/writing VCF HOT 3
- VCF files with spaces in the file name cannot be read HOT 4
- configure sparkSession with glow HOT 2
- VEP exone/intron annotations failure HOT 5
- Improve handling of environment variables in the pipe transformer HOT 5
- Installing and running glow outside of databricks HOT 11
- Release with spark3.2 support HOT 1
- Vulnerable shared library might make glow-spark3 vulnerable. Can you help upgrade to patch versions? HOT 5
- Docker build.sh script is not current in tagged release HOT 1
- Ask: add glow to chocolatey HOT 4
- VCF Infinity/NaN values are not handled according to VCF spec
- PySpark 3.3 support HOT 8
- Load glow mave package from Python HOT 5
- spark.read.format("vcf").load() fails for vcf.bgz files HOT 3
- Cannot write INFO fields with LongType to VCF HOT 2
- Python tests fail with KeyError: '_glow_regression_values' HOT 1
- Logistic regression ValueError: Null fit failed! HOT 2
- AnalysisException: Column 'num_workers' does not exist. HOT 1
- pipe transformer support for file input/output for command line apps HOT 2
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