Scalable Tools for Computational Biology
Introduction
Tools for indexing and searching terabytes of genomic and transcriptomic data
Summary
Scientists need tools for quickly indexing, searching, and analyzing terabytes, or even petabytes, of raw genomic and trancriptomic data. This project is developing multiple tools for efficiently representing biological data so that huge data sets can be processed in RAM, providing orders-of-magnitude increases in scalability and performance. This project has produced several open-source tools.- Squeakr, a fast and compact CQF-based k-mer counter for computational biology applications.
- deBGR, a compact nearly exact representation of de Bruijn graphs of k-mers.
- Mantis, an indexing system for searching for sequences in large-scale databases of genomic and transcriptomic data.
News
- Our 2021 bioRxiv preprint describes how to combine Mantis with LSM trees to create a scalable and incrementally updatable index on raw sequencing data.
Researchers
Palo Alto, CA, US
External Researchers
- Fatemeh Almodaresi
- Michael A. Bender
- Mike Ferdman
- Rob Patro
Related Publications
- VariantStore: an index for large-scale genomic variant search July, 2021
- An Incrementally Updatable and Scalable System for Large-Scale Sequence Search using LSM Trees February, 2021
- An Efficient and Scalable Representation of High-Dimensional Color Information Enabled via de Bruijn Graph Search May, 2019
- An Efficient, Scalable and Exact Representation of High-Dimensional Color Information Enabled via de Bruijn Graph Search 2019
Category
- Active Research Projects