Led by Blake Joyce, CyVerse, BIO5 Institute
In the past, researchers have all but assumed that once data was generated, it would be assessed, analyzed, and visualized properly. It is unclear whether this assumption was ever valid, but in the age of 'big data' it simply does not work in the face of massive, messy, multidimensional datasets. Additionally, advanced and interactive visualizations hold the promise of greater result reproducibility, clarity of message, provenance, and generating data sets that researchers can assess/analyze on the fly instead of relying on static images. Best of all: there are many free advanced visualization software packages available to researchers. As an introduction to this topic, we will discuss advanced visualizations and use Plotly in Python to assess genetics data. All code and slide materials can be found in the parent GitHub repo.