UCSC Xena

Mentors: Student: Ayan Banerjee

<p>UCSC Xena is a functional genomics visualization and analysis platform. For this (genomics visualization and analysis), there are many datasets which are provided by data hubs available with Xenabrowser itself which users can use. The data hubs are: UCSC Public Hub, TCGA Hub, Pan-Cancer Atlas Hub, ICGC Hub, UCSC Toil RNAseq Recompute, Treehouse Hub and GDC Hub. Our discussion of interest lies in GDC Hub.</p> <p>GDC (Genomic Data Commons) Hub fetches data from the GDC repository: <a href="https://portal.gdc.cancer.gov/repository" target="_blank">https://portal.gdc.cancer.gov/repository</a> via the GDC API. However, the data on the Xena is not updated. Current Xena data was updated on release 10, roughly 1.5 yrs ago. This project mainly revolves around updating data on xena with the current release (release 15). This will also simplify the process of adding data to Xena removing the XML files as a source.</p>

Mentors: Student: Kristupas Repečka

<p>In order to visualize their private datasets, users of UCSC Xena browser have to upload data using separate desktop application. This behavior does not fit preferred workflow, since all visualizations are carried out in the browser and using desktop client only for uploading data is confusing for some users.</p> <p>The goal of this project is to move existing data upload functionality from desktop client to the browser. In addition to that, import module would be improved with extensive error handling and uniformed user experience overall.</p>

Mentors: Student: Akhil Kamath

<p>Currently UCSC Xena is designed in such a way that each row is a sample and columns are data types. Biologists often need to study the different versions of a gene called transcripts. Transcripts are important because an increase in the abundance of one of the versions may lead or drive cancer. This project aims at building a new application where the rows will be transcripts and columns will be data types about that transcript. Both the applications will then be linked giving users a smooth toggle between the sample centric and transcript centric views about the same underlying data. The project also proposes to blend the visual spreadsheet view and the chart view in a way that a column will plot the transcript expressions across a set of samples.</p>