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DivBrowse-interactive visualization and exploratory data analysis of variant call matrices.

Patrick KönigSebastian BeierMartin MascherNils SteinMatthias LangeUwe Scholz
Published in: GigaScience (2023)
DivBrowse offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data by including features like interactive calculation of variant frequencies and principal component analysis. The use of established standard file formats for data input supports interoperability and seamless deployment of application instances based on the data output of established bioinformatics pipelines.
Keyphrases
  • electronic health record
  • big data
  • gene expression
  • machine learning
  • copy number
  • transcription factor
  • genome wide
  • single cell
  • rna seq
  • deep learning