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.

Documentation

Links