Variant Data Manipulation

Glow offers functionalities to extract, transform and load (ETL) genomic variant data into Spark DataFrames, enabling seamless manipulation, filtering, quality control and transformation between file formats.

• Read and Write VCF, Plink, and BGEN with Spark
  • VCF
  • BGEN
  • PLINK
• Read Genome Annotations (GFF3) as a Spark DataFrame
  • Schema
• Create a Genomics Delta Lake
  • VCF to Delta Lake table notebook
• Variant Quality Control
  • Notebook
• Sample Quality Control
  • Computing user-defined sample QC metrics
• Liftover
  • Create a liftOver cluster
  • Coordinate liftOver
  • Variant liftOver
• Variant Normalization
  • normalize_variants Transformer
  • Usage
  • Options
  • normalize_variant Function
• Split Multiallelic Variants
  • Usage
• Merging Variant Datasets
  • Aggregating INFO fields
  • Joint genotyping
• Hail Interoperation
  • Create a Hail cluster
  • Convert to a Glow DataFrame
  • Schema mapping
• Utility Functions
  • Struct transformations
  • Spark ML transformations
  • Variant data transformations