Distributed Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (DiBELLA) v1.0.0
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
We present a parallel algorithm and scalable implementation for genome analysis, specifically the problem of finding overlaps and alignments for data from "third generation" long read sequencers. While long sequences of DNA offer enormous advantages for biological analysis and insight, current long read sequencing instruments have high error rates and therefore require different approaches to analysis than their short read counterparts. Our work focuses on an efficient distributed-memory parallelization of an accurate single-node algorithm for overlapping and aligning long reads. We achieve scalability of this irregular algorithm by addressing the competing issues of increasing parallelism, minimizing communication, constraining the memory footprint, and ensuring good load balance. The resulting application, DiBELLA, is the first distributed memory overlapper and aligner specifically designed for long reads and parallel scalability.
- Short Name / Acronym:
- Distributed Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper
- Project Type:
- Open Source, No Publicly Available Repository
- Site Accession Number:
- 2020-158
- Software Type:
- Scientific
- License(s):
- BSD 3-clause "New" or "Revised" License
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE; Oak Ridge National LaboratoryPrimary Award/Contract Number:AC02-05CH11231
- DOE Contract Number:
- AC02-05CH11231
- Code ID:
- 52870
- OSTI ID:
- code-52870
- Country of Origin:
- United States
Similar Records
diBELLA: Distributed Long Read to Long Read Alignment
Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (BELLA) v1.0
Conference
·
Mon Dec 31 23:00:00 EST 2018
·
OSTI ID:1602840
Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (BELLA) v1.0
Software
·
Tue May 08 20:00:00 EDT 2018
·
OSTI ID:code-17092