ELaSTIC
ELaSTIC is a software suite for a rapid identification and clustering of similar sequences from large-scale biological sequence collections. At its core is an efficient MinHash-based strategy to detect similar sequence pairs without aligning all sequences against each other.
In this web site you can find out more about the project,
download the source code, and access the documentation.
Get the most recent version !!!
News
May 7, 2017: Version 1.90 is now available. We integrated ELaSTIC with Parasail to drastically improve througput of the validation stage.
February 11, 2016: Finally a new release with several performance improvements!
December 3, 2014: We are working with the Argonne ALCF team to further improve scalability of ELaSTIC.
About ELaSTIC
ELaSTIC is an open source software suite for a rapid identification and clustering of similar sequences from large-scale biological sequence collections. It is designed to work with data sets consisting of millions of DNA/RNA or amino acid strings, using various alignment criteria.
Thanks to the clever use of the MinHash and sketching technique, and the application of carefully engineered parallel algorithms, ELaSTIC is extremely efficient and scalable while maintaining sensitivity. Thanks to its modular design, it can be easily combined with other tools, like MCL, for the downstream analysis.
ELaSTIC consists of a set of sequential and parallel tools that can be organized into an end-to-end similarity detection and clustering workflow. Its most time consuming component, the graph construction procedure, can be executed on large distributed memory clusters and supercomputers for maximum efficiency.
ELaSTIC is licensed under the MIT License with some components covered by the Boost Software License.
ELasTIC has been developed by Jaroslaw Zola.
Read ELaSTIC documentation to get detailed overview of the suite.
Download
The current release is ELaSTIC 1.90, and the tarball is available here.
The ELaSTIC source code is hosted at the GitLab repository.
You can obtain the pre-release updates using git:
git clone git@gitlab.com:SCoRe-Group/ELaSTIC.git
Documentation
Note that we are still working to extend the documentation. Nevertheless, it is a good starting point if you want to use ELaSTIC!
The current version of ELaSTIC documentation is provided in this web page.
You can download a PDF version as well.
Citing
If you find ELaSTIC useful in your research, please cite:
- J. Zola, "Constructing Similarity Graphs from Large-scale Biological Sequence Collections", In Proc. IEEE International Workshop on High Performance Computational Biology (HiCOMB), 2014.
You can refer to our earlier publications as well:
- X. Yang, J. Zola, S. Aluru, "Large-Scale Metagenomic Clustering on Map-Reduce Clusters", In Journal of Bioinformatics and Computational Biology, vol. 11, no. 1, pp. 1340001, 2013.
- X. Yang, J. Zola, S. Aluru, "Parallel Metagenomic Sequence Clustering Via Sketching and Maximal Quasi-clique Enumeration on Map-Reduce Clouds", In Proc. IEEE Int. Parallel and Distributed Processing Symposium (IPDPS), pp. 1223-1233, 2011.
Contact
If you have questions regarding ELaSTIC or you would like to see specific features added or you would like to build a collaboration around it, please contact Jaroslaw 'Jaric' Zola.