@phdthesis{Ginzel2019,
  author    = {Sebastian Ginzel},
  title     = {Enabling Versatile And Comprehensive Analysis Of Genomic Variant Data},
  address   = {D{\"u}sseldorf},
  pages     = {xii, 174},
  year      = {2019},
  abstract  = {The initially large number of variants is reduced by applying custom variant annotation and filtering procedures. This requires complex software toolchains to be set up and data sources to be integrated. Furthermore, increasing study sizes subsequently require higher efforts to manage datasets in a multi-user and multi-institution environment. It is common practice to expect numerous iterations of continuative respecification and refinement of filter strategies, when the cause for a disease or phenotype is unknown. Data analysis support during this phase is fundamental, because handling the large volume of data is not possible or inadequate for users with limited computer literacy. Constant feedback and communication is necessary when filter parameters are adjusted or the study grows with additional samples. Consequently, variant filtering and interpretation becomes time-consuming and hinders a dynamic and explorative data analysis by experts.},
  language  = {en}
}