General Information
| Description | Condensing redundant reads from high-throughput sequencing studies |
| Homepage | http://pringlelab.stanford.edu/protocols.html |
Publications
Fulcrum: condensing redundant reads from high-throughput sequencing studies
Motivation:
Ultra-high-throughput sequencing produces duplicate and near-duplicate reads, which can consume computational resources in downstream applications. A tool that collapses such reads should reduce storage and assembly complications and costs.
Results:
We developed Fulcrum to collapse identical and near-identical Illumina and 454 reads (such as those from PCR clones) into single error-corrected sequences; it can process paired-end as well as single-end reads. Fulcrum is customizable and can be deployed on a single machine, a local network or a commercially available MapReduce cluster, and it has been optimized to maximize ease-of-use, cross-platform compatibility and future scalability. Sequence datasets have been collapsed by up to 71%, and the reduced number and improved quality of the resulting sequences allow assemblers to produce longer contigs while using less memory.
Availability and implementation:
Source code and a tutorial are available at http://pringlelab.stanford.edu/protocols.html under a BSD-like license. Fulcrum was written and tested in Python 2.6, and the single-machine and local-network modes depend on a modified version of the Parallel Python library (provided).
Contact:
erik.m.lehnert@gmail.com
Supplementary information:
Supplementary information is available at Bioinformatics online.
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