Genome Guild

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Inspiration

We wanted to develop a process that would securely transfer genomic data between parties/institutions. Find a way to truly randomize generation of encryption key.

What it does

Our program addresses two issues: data security and data encryption. Data Security We developed a log in GUI to showcase how someone at an institution would access the data. For example, a lab tech would have the security to upload data, but they would not have the security to download or edit the data. Data Encryption We took a hybrid encryption method where we used both symmetric and asymmetric encryption. For the symmetric encryption we utilize an open source tool called Cryfa which is a tool that helps encrypt our data using a symmetric key. This tool also compresses FASTA/FASTQ sequences by a factor of three which allows an efficient way for managing the genomic data within the data warehouse. We used asymmetric encryption to create a public and private key for our symmetric key to allow another layer of encryption.

How we built it

We built our program in Python and R. We also utilized an open source genomic encryption tool called Cryfa. In order to interact with this tool, we had to use the Anaconda command line. Python was used to develop the hybrid encryption method while R was used for the establishment of data security levels and a GUI.

Challenges we ran into

-Time constraints -Memory allocation

Accomplishments that we're proud of

-Creating an interactive GUI to showcase our ideas for data security -Creating a hybrid encryption method without compromising the data -Coming up with a method to generate a symmetric key using data that is randomly generated based on nematode movement data

What we learned

-The management of the life style of genomic data is a multi-layer issue. From ethical complexities to collaboration among colleagues there are multiple avenues or areas that we could have

What's next for Genome Guild

-We would further develop our method for generating a symmetric key using nematode data. Currently, we have developed a method, but due to a lack of publicly available data we cannot currently develop or run the code to do so. -We would further develop the GUI to incorporate opportunities for more clinical research, and other professionals to utilize the service.