Abstract. Depending on the experiment and hypothesis, many kinds of genomic data are collected and, in the face of varying precision and experimental conditions, a one-size-fits-all approach does not exist. Even several-sizes-fit-most is optimistic. It is very difficult to universally address the challenge of visualizing heterogenous genomic data.
Many conventional approaches to specific data tasks are used – from legacy schemes to modern takes on typical encodings. I will survey data analysis tasks whose visual solutions are either lagging or unstandardized and attempt to identify opportunities for tool creators to contribute to the field.
Martin Krzywinski (website) is known for his work in bioinformatics, data visualization and the interface of science and art. He applies design, both data and artistic, to assist discovery, explanation and engagement with scientific data and concepts. His information graphics have appeared in the New York Times, Wired, Scientific American and covers of numerous books and scientific journals such as Nature and Genome Research.