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Optimize cost
While sequencing costs have fallen, costs associated with compute and storage have
grown as organizations continues to increase throughput and explore more data -
heavy applications, such as single - cell genomics. In contrast to on - premises setups
that require large upfront investments and continuous CapEx , AWS enables genomics
organization to use only what they need, when they need it.
AWS offers storage and compute offerings at a variety of price points. Services such as
Amazon EC2 Spot Instances offer up to 90 precent discounts in comparison to on -
demand compute prices. For long - term storage of infrequently used data, Amazon S3
Glacier provides secure data archiving starting at $1 per terabyte per month.
Genomics organizations also leverage AWS to reduce development and operational
costs. By building its AI - based genomics intelligence platform on AWS, Emedgene
reduced its costs of applying artificial intelligence to big genomics by 70 percent while
accelerating model development and optimization.
Reduce time to discovery
Genomics is a data - heavy discipline requiring extensive compute resources to analyze
samples and extract meaningful insights.
To accelerate discoveries, AWS offers a robust suite of powerful compute and machine
learning options that enable scientists to process more samples, run more complex
analyses, and query at - scale. The only cloud provider to deliver 100 Gbps of
networking throughput, AWS delivers high - throughput data ingestion, analysis, and
interpretation services and tools designed to help genomics organizations get more
from their data.
Genomics organizations such as Fauna Bio leverage the robust computation power of
AWS to analyze multi - omic datasets, accelerate research, and uncover new
discoveries.
Accelerate data analysis
With native integration to workflow tools, including Nextflow and Cromwell,
organizations can orchestra AWS Batch processes to accelerate processing time for
computational analysis. For example, with AWS Fred Hutch was able to reduce
compute time from seven years down to seven days, accelerating the organizations
research on developing therapeutics to fight cancer.
Simplify data interpretation
The full value of genomic data is recognized once its put into context. Population
genomics programs across the globe leverage the security, flexibility, and scalability of
AWS to host population - scale biobanks and provide democratized access to the
industry. Using querying and machine learning services from AWS, scientists can
rapidly query datasets, including the Cancer Genome Atlas (TCGA) and the Broad
Institute's Genome Aggregation Database (gnomAD) hosted on AWS registry of open
data , to rapidly extract insights and answers.
Munich Leukemia Lab
Uses AWS FPGAs to
Reduce Genome - Data
Processing Time from
20 hours to >
3 hours
Dedicate 20%
more IT resources
to software
development
70% c ost reduction
for AI implementation
using AWS
