ElasticBLAST is a new tool that helps you run BLAST searches on the cloud. ElasticBLAST is perfect for you if you have thousands to millions of queries to our Basic Local Alignment Search Tool (BLAST ®), or if you want to use cloud infrastructure for your searches. ElasticBLAST can handle large searches that are not appropriate for NCBI web BLAST, and it runs them more quickly than stand-alone BLAST+.

ElasticBLAST works on two of the current NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) partners- Amazon Web Services (AWS) and Google Cloud Platform (GCP).  ElasticBLAST works by distributing your searches across multiple cloud instances to process them in tandem. The ability to scale resources in this way allows you to process large numbers of queries in a shorter time than you could with BLAST+. ElasticBLAST can handle millions of queries, and it also supports most BLAST+ options and programs.

Making it easier to run BLAST on the cloud

ElasticBLAST reduces the barrier to using the cloud by creating and managing cloud resources for you. It manages the software and database installation, handles partitioning of the BLAST workload among the various instances and deallocates cloud resources when the searches are done. For example, ElasticBLAST will select the best cloud instance type for your search based on the database metadata that provides database size and memory needs (Figure 1). You can also manually select the instance type if you prefer.

Fig. 1: JSON metadata for the 16S_ribosomal_RNA database. The “bytes-to-cache” information helps ElasticBLAST pick out an instance with the appropriate capacity.

Selecting Databases

ElasticBLAST can access the 28 NCBI databases available on AWS and GCP. These are the same databases that are also available from the NCBI FTP site. For instance, databases available on the two cloud providers include the RefSeq Eukaryotic Representative Genomes database, 16S database based on Targeted Loci, and Human and mouse genomes databases.

You can also provide your own databases, and you can produce the metadata needed to select an instance through a Python script that comes with ElasticBLAST.

Example Runs

ElasticBLAST can perform a variety of searches with query sets that range from hundreds to millions of sequences and BLAST databases of all sizes.  Table 1 shows ElasticBLAST searches with query sets that range up to billions of letters using a variety of BLAST databases.

Table 1: Sample ElasticBLAST searches.  This table demonstrates the breadth of searches supported by ElasticBLAST.  Additionally, the first row demonstrates the ability of ElasticBLAST to use many CPUs (3200) on a cloud provider at once to complete a task in hours that would have taken days on a single machine.

Costs

Because ElasticBLAST runs on cloud providers, using it will incur some cost. Based on current cost structures on AWS and GCP, in most cases these costs are quite small. For example, a protein search with a query of about 20 million residues against a database of about 20 billion residues can cost less than $5. Even a larger search with a query of 3-4 billion DNA bases can cost only around $50. Both cloud services include the option to bid on instances for less than full price, which can result in significant savings. ElasticBLAST can be configured to request such instances. Your costs will obviously vary based on many factors, and we encourage you to explore these options with the individual cloud providers. Also, both AWS and GCP offer a free tier or time-limited trial of their cloud services, and you can find information about using ElasticBLAST with the free tiers here.

Welcome to ElasticBLAST!

Go ahead and run your first ElasticBLAST search! We are sure you’ll love how ElasticBLAST accelerates your research.

Your feedback is crucial to the development and support of ElasticBLAST. If you have any questions or suggestions, please reach out to us at [email protected]. We’d love to hear from you.

ElasticBLAST is a cloud-native package developed by the National Center for Biotechnology Information (NCBI) at the National Library of Medicine (NLM) with support from the NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) Initiative.