breseq_bam2aln
breseq_bam2aln identifies structural variations in microbial genomes from DNA resequencing data to characterize new junctions and deleted regions and their impacts on genes.
Key Features:
- Structural Variation Detection: Identifies deletions, insertions, and rearrangements mediated by mobile genetic elements or repetitive sequences by evaluating new sequence junctions with split-read alignments to a reference genome and incorporating matches to repeat sequences.
- Statistical Model Integration: Employs a statistical model of read coverage evenness to validate structural variation predictions and reduce false positives.
- Comprehensive Mutation Descriptions: Combines predicted new junctions and deleted chromosomal regions to produce biologically relevant descriptions of mutations and their effects on genes.
- Performance on Simulations: Demonstrated on simulated Escherichia coli genomes to recover unique breakpoint sequences and mobile element insertions at modest read-depth coverage (>40-fold).
Scientific Applications:
- Microbial Epidemiology: Tracks genomic changes that contribute to pathogenic traits or shifts in microbial lifestyle.
- Experimental Evolution: Identifies spontaneous structural mutations to elucidate the genetic basis of adaptive changes.
- Synthetic Biology and Genetics: Detects unintended genomic alterations in engineered organisms to assess genomic integrity.
Methodology:
Processes high-throughput DNA resequencing data using split-read alignments to a reference genome with explicit matching to repeat sequences, applies a statistical model of read coverage evenness to validate predictions, and combines predicted new junctions and deleted chromosomal regions to describe mutation impacts; performance was evaluated on simulated Escherichia coli genomes at >40-fold coverage.
Topics
Collections
Details
- Maturity:
- Mature
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 12/19/2016
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
Sequence alignment
Outputs
Publications
Barrick JE, Colburn G, Deatherage DE, Traverse CC, Strand MD, Borges JJ, Knoester DB, Reba A, Meyer AG. Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq. BMC Genomics. 2014;15(1):1039. doi:10.1186/1471-2164-15-1039. PMID:25432719. PMCID:PMC4300727.
Afgan E, Baker D, van den Beek M, Blankenberg D, Bouvier D, Čech M, Chilton J, Clements D, Coraor N, Eberhard C, Grüning B, Guerler A, Hillman-Jackson J, Von Kuster G, Rasche E, Soranzo N, Turaga N, Taylor J, Nekrutenko A, Goecks J. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Research. 2016;44(W1):W3-W10. doi:10.1093/nar/gkw343. PMID:27137889. PMCID:PMC4987906.
Mareuil F, Doppelt-Azeroual O, Ménager H. A public Galaxy platform at Pasteur used as an execution engine for web services. Unknown Journal. 2017. doi:10.7490/f1000research.1114334.1.