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Processing genome-wide association studies within a repository of heterogeneous genomic datasets.

Anna BernasconiArif CanakogluFederico Comolli
Published in: BMC genomic data (2023)
As a result of the our work on GWAS datasets, we enable 1) their interoperable use with several other homogenized and processed genomic datasets in the context of the META-BASE repository; 2) their big data processing by means of the GenoMetric Query Language and associated system. Future large-scale tertiary data analysis may extensively benefit from the addition of GWAS results to inform several different downstream analysis workflows.
Keyphrases
  • big data
  • data analysis
  • genome wide association
  • rna seq
  • artificial intelligence
  • machine learning
  • copy number
  • multidrug resistant
  • single cell
  • gene expression
  • genome wide association study
  • deep learning