Featured Speakers and Demos

The Sci/Tech Webinar features:

Katy Börner and Andreas Bueckle, Indiana University, Bloomington
Presenting the Registration User Interface (RUI) and Visible Human Massive Open Online Course (VHMOOC)

In this two-part presentation, Katy and Andreas will be presenting the Visible Human Massive Open Online Course (VHMOOC), and then demonstrating the Registration User Interface (RUI).

The Visible Human Massive Open Online Course (VHMOOC) is a free, remote, asynchronous class featuring videos, readings, and exercises highlighting various aspects of HuBMAP. It is designed as a hub to bring together all people interested in HuBMAP from every point on the novice-expert continuum. The course covers topics such as data generation, ontology usage, common coordinate design, and computational infrastructure components such as the HuBMAP portal and user interfaces. In their presentation, Katy and Andreas will also discuss the learning objectives of the VHMOOC and how it can be used in existing classes and professional training. Last but not least, they will discuss plans for future extensions of the VHMOOC. You can read more about the VHMOOC here.

The RUI was developed to allow stakeholders in HuBMAP to register tissue blocks, i.e., to record the size, position, and orientation of human tissue data with regards to 3D reference organs. The RUI has been used by tissue mapping centers (TMCs) across the HuBMAP consortium to register a total of 45 kidney and spleen tissue blocks to date, with planned support for 17 organs in the future. Based on a recently conducted study, users were able to achieve a median accuracy of 1.3 mm for position, 5.9 degrees for rotation, and a completion time of 22.6 seconds after eight identical registration tasks using a Desktop version of the RUI. These results, together with low costs and easy deployment, indicate that the RUI is well-suited for allowing users in HuBMAP to register tissue blocks at sufficient accuracy and speed. Katy and Andreas will cover the design specifications of the RUI and share MC-IU's plans for its future development. The most recent version of the RUI is available here.

Rahul Satija, New York Genome Center
Azimuth Demo

In his presentation, Rahul will be demonstrating Azimuth, which is a web application that uses an annotated reference dataset to automate the processing, analysis, and interpretation of a new single-cell RNA-seq experiment. Azimuth leverages a 'reference-based mapping' pipeline that inputs a counts matrix of gene expression in single cells, and performs normalization, visualization, cell annotation, and differential expression (biomarker discovery). All results can be explored within the app, and easily downloaded for additional downstream analysis.