Every week on Friday, when the core team of Orange developers meets, we are designing new improvements of Orange’s graphical interface. This time, it was the status bar. Well, actually, it was the status bar quite a while ago and required the change of the core widget library, but it is materializing these days and you will see the changes in the next release.
Consider the Neighbors widget. The widget considers the input data and reference data items, and outputs instance form input data that are most similar to the references. Like, if the dolphin is a reference, we would like to know which are the three most similar animals. But this is not what want I wanted to write about. I would only like to say that we are making a slight change in the user interface. Below is the Neighbors widget in the current release of Orange, and the upcoming one.
See the difference? We are getting rid of the infobox on the top of the control tab, and moving it to the status bar. In the infobox widgets typically display what is in their input and what is on the output after the data has been processed. Moving this information to the status bar will make widgets more compact and less cluttered. We will similarly change the infoboxes in this way in all of the widgets.
Molecular biologists have in the past twenty years invented technologies that can collect abundant experimental data. One such technique is single-cell RNA-seq, which, very simplified, can measure the activity of genes in possibly large collections of cells. The interpretation of such data can tell us about the heterogeneity of cells, cell types, or provide information on their development.
Typical analysis toolboxes for single-cell data are available in R and Python and, most notably, include Seurat and scanpy, but they lack interactive visualizations and simplicity of Orange. Since the fall of 2017, we have been developing an extension of Orange, which is now (almost) ready. It has even been packed into its own installer. The first real test of the software was in early 2018 through a one day workshop at Janelia Research Campus. On March 6, and with a much more refined version of the software, we have now repeated the hands-on workshop at the University of Pavia.
The five-hour workshop covered both the essentials of data analysis and single cell analytics. The topics included data preprocessing, clustering, and two-dimensional embedding, as well as working with marker genes, differential expression analysis, and interpretation of clusters through gene ontology analysis.
I want to thank Prof. Dr. Riccardo Bellazzi and his team for the organization, and Erasmus program for financial support. I have been a frequent guest to Pavia, and learn something new every time I am there. Besides meeting new students and colleagues that attended the workshop and hearing about their data analysis challenges, this time I have also learned about a dish I had never had before in all my Italian travels. For one of the dinners (thank you, Michela) we had Pizzoccheri. Simply great!