SBARS
SBARS identifies long repeats in chromosome-scale DNA by transforming nucleotide sequences into functional representations and applying spectral-based analysis for structural genomic characterization.
Key Features:
- Spectral Methodology: SBARS applies a spectral-based technique to functions derived from nucleotide sequences to detect repeated DNA structures.
- Functional Sequence Representation: SBARS transforms nucleotide sequences into functional representations to enable analysis without directly processing raw sequence strings.
- Multi-scale Analysis: The approach supports examination of nucleotide sequence structures across different scales, enabling detection of repeats comparable in size to chromosomes.
- Efficient Dotplot Computation: SBARS leverages spectral computations to reduce the time complexity of creating dotplots for large genomic sequences.
- Long-repeat Detection in Chromosome-sized Sequences: SBARS targets identification of various types of long repeats within sequences comparable to chromosomes and whole genomes.
Scientific Applications:
- Chromosome and Genome Analysis: Facilitates identification and structural characterization of long repeats within large DNA fragments such as chromosomes and whole genomes.
- Comparative Genomics: Enables comparative analyses of chromosome-scale sequences by detecting structural repetitions and variations relevant to genomic comparison.
Methodology:
Transform nucleotide sequences into functional representations, apply spectral-based analysis to those functions to detect repeated structures across scales, and use spectral computations to accelerate dotplot construction and reduce time complexity.
Topics
Details
- Tool Type:
- desktop application
- Operating Systems:
- Linux, Windows
- Programming Languages:
- C++
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Pyatkov MI, Pankratov AN. SBARS: fast creation of dotplots for DNA sequences on different scales using GA-,GC-content. Bioinformatics. 2014;30(12):1765-1766. doi:10.1093/bioinformatics/btu095. PMID:24532721.
PMID: 24532721