Mission Bio Unlocks Single-Cell Cancer Data Insights Using AWS
The tens of trillions of cells in the human body share many characteristics, but they can differ in a surprising number of ways. By sequencing at a single-cell level rather than gathering aggregate information about an entire sample, researchers can examine each cell’s specific mutations, protein expression, and interaction with the cellular environment. These single-cell insights can help researchers and doctors answer important questions about human health, such as why some tumors do or do not respond to a given chemotherapy.
Mission Bio's Tapestri platform allows scientists to obtain and analyze multiomic data—information about cellular DNA, proteins, and more—from thousands of individual cells. In addition to the microfluidic instruments that prepare samples for multiomic data collection, the Tapestri workflow also includes cloud-based analytics and visualization tools built on Amazon Web Services (AWS) to get the most out of that data.
“I often say the genomic analysis technologies we have today are like an optical microscope, whereas Mission Bio’s Tapestri platform is like an electron microscope by comparison,” says Niranjan Vissa, director of software engineering at Mission Bio. “The Tapestri platform yields a lot more data, and the data is more useful. But it is new data, and it takes a while for people to understand it completely.”
The integrated Tapestri analysis pipeline that will facilitate this understanding is built entirely on AWS. Mission Bio believes that the Tapestri platform will give researchers the multidimensional information needed to construct a comprehensive understanding of cancer biology. The ultimate goal is for these biological insights to lead to treatments that will eventually eradicate the disease entirely and unlock other advances in human health.
AWS is as critical to us as electricity or water. Data analysis is central to everything we do, both internally and for our customers."
Director of Software Engineering, Mission Bio
Powering the Single-Cell Resolution Revolution on AWS
Without AWS, Vissa estimates that Mission Bio would have to spend millions of dollars on servers, computing clusters, and technicians. “We thought about doing it all ourselves, and then we laughed and gave up on the idea,” Vissa says. “It just doesn’t make sense, especially for a small company like Mission Bio. We don’t want to spend our money and time on undifferentiated heavy lifting; we’d rather focus on the value that our technology brings.”
Data uploads and hosting are enabled by Amazon Simple Storage Service (Amazon S3), an object storage service. Researchers can conduct complex analyses using Amazon Elastic Compute Cloud (Amazon EC2), a web service that provides secure, resizable compute capacity in the cloud, with output information written to and managed within the Amazon Relational Database Service (Amazon RDS). Building on AWS allows the company to be highly scalable and efficient in delivering the best possible service to its research customers.
Vissa points to data ingestion as one of the key points where AWS dramatically improves user experience for Mission Bio’s customers. When most people think of analyzing genomic data in the cloud, they think about the sheer cloud computing power that is needed. But before that analysis happens, the data must be transferred into the cloud in what is often an extremely slow, frustrating process. But thanks to features of Amazon S3, such as high security and geography-specific transfer acceleration, researchers can upload large FastQ files—genomic datasets—from their own devices with confidence and relative ease via secure sign-in with Amazon Cognito, an access control tool for web and mobile apps. Customers can also be confident that their data will be properly configured for analysis because all ingested data are validated using AWS Batch, which dynamically provisions optimal compute resources, before being stored in Amazon S3.
Growing with AWS
Mission Bio will soon transition to using Amazon EC2 Spot Instances, which are available at up to a 90 percent discount compared to On-Demand pricing, for many of the Tapestri pipeline’s compute processes. Vissa estimates that the company stands to realize overall cost savings of up to 70 percent from this change.
“AWS has grown with us, or rather we have grown with AWS very easily—it is as critical to us as electricity or water,” Vissa says. “Data analysis is central to everything we do, both internally and for our customers, so AWS is essential in every way.”
As the company’s analytical capabilities continue to grow, it is expanding the applications of their platform. Mission Bio started by analyzing blood cancer cells and is now moving into more difficult problems such as solid tumor analysis, which requires the ability to clean and process noisy data gathered from what are often small, low-quality samples. Soon the company will be addressing every type of cancer, yielding key insights that will push the field of cancer research and other human health applications into the future.
See how AWS is supporting other life science companies in their quest to improve human health.
About Mission Bio
Mission Bio has developed a precision genomics platform designed to provide single-cell DNA sequencing at single-base resolution, enabling researchers and clinicians to unlock single-cell biology to accelerate the discovery, development, and delivery of precision medicine.
Benefits of AWS
- Reduced compute costs by 70 percent
- Streamlined ingestion of large FastQ data files to improve user experience
- Enabled scalable processing of multiomic data
- Hosted large genomic datasets and analytical outputs for easy access
AWS Services Used
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.
Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance.
Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.
AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS.
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