Quality Metrics to Guide Visual Analysis of High Dimensional Genomics Data

Sara Johansson Fernstad, Alexander Macquisten, Janet Berrington, Nicholas Embleton, Christopher Stewart
2020 International EuroVis Workshop on Visual Analytics  
Studies of genome sequenced data are increasingly common in many domains. Technological advances enable detection of hundreds of thousands of biological entities in samples, resulting in extremely high dimensional data. To enable exploration and understanding of such data, efficient visual analysis approaches are needed that take domain and data specific requirements into account. Based on a survey with bioscience experts, this paper suggests a categorisation and a set of quality metrics to
more » ... lity metrics to identify patterns of interest, which can be used as guidance in visual analysis, as demonstrated in the paper.
doi:10.2312/eurova.20201083 dblp:conf/eurova-ws/FernstadMBES20 fatcat:qk6mn7focjdnjbfyq4gneck3x4