FNBtools
FNBtools identifies homozygous causal deletions in mutant populations from next-generation sequencing (NGS) data to enable mapping of genotype–phenotype relationships.
Key Features:
- Population-scale deletion detection: Identifies homozygous deletions across entire mutant populations using NGS data.
- High accuracy across coverage levels: Maintains high sensitivity and specificity across different sequencing coverage levels.
- Detection of small and large deletions: Detects both small and large deletions that are causal in mutant populations.
- Unique deletion identification: Filters out deletions present in wild-type or control pools to pinpoint unique deletions within mutant pools.
- Genome-wide visualization: Produces Circos-based genome-wide visualizations of identified deletions.
- Benchmarking performance: Outperforms existing popular deletion callers for small-deletion detection across coverage levels as demonstrated by simulated-data analyses.
Scientific Applications:
- Functional genomics and genetics: Facilitates forward and reverse genetics studies using deletion mutagenesis methods such as fast neutron bombardment (FNB) to link deletions to phenotypes.
- Case study—Medicago truncatula salt tolerance: Applied to a salt-tolerant Medicago truncatula mutant to identify a unique deletion locus that was validated by PCR amplification, sequencing, and genetic linkage analyses.
Methodology:
Analyzes NGS data to detect homozygous deletions at population scale, filters deletions against wild-type/control pools to identify unique events, generates Circos visualizations, and was benchmarked using simulated-data analyses showing improved sensitivity and specificity for small and large deletions.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Mac
- Programming Languages:
- Perl
- Added:
- 7/29/2018
- Last Updated:
- 10/14/2021
Operations
Publications
Sun L, Ge Y, Bancroft AC, Cheng X, Wen J. FNBtools: A Software to Identify Homozygous Lesions in Deletion Mutant Populations. Frontiers in Plant Science. 2018;9. doi:10.3389/fpls.2018.00976. PMID:30042776. PMCID:PMC6048286.