Computational detection of significant variation in binding affinity across two sets of sequences with application to the analysis of replication origins in yeast
2008

SADMAMA: A Tool for Analyzing DNA Binding Affinity Variations

publication Evidence: moderate

Author Information

Author(s): Keich Uri, Gao Hong, Garretson Jeffrey S, Bhaskar Anand, Liachko Ivan, Donato Justin, Tye Bik K

Primary Institution: Cornell University

Hypothesis

Is one set of DNA sequences significantly enriched in binding sites compared to another set?

Conclusion

SADMAMA effectively identifies significant differences in binding site quality and quantity between DNA sequence sets.

Supporting Evidence

  • SADMAMA provides plausible explanations for differential ARS activity observed in previous experiments.
  • The tool suggests that multiple weak binding sites can contribute to effective DNA replication.
  • SADMAMA's bootstrap approach helps avoid false positives in statistical testing.

Takeaway

The study created a tool called SADMAMA that helps scientists understand how well certain DNA sequences can bind to proteins, which is important for DNA replication.

Methodology

SADMAMA uses statistical tests, including bootstrapping and simplified models, to assess differences in binding site frequency and quality between two sets of sequences.

Limitations

The tool assumes independence of input sequences and may not handle phylogenetically related sequences well.

Statistical Information

P-Value

0.007

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1186/1471-2105-9-372

Want to read the original?

Access the complete publication on the publisher's website

View Original Publication