Understanding Co-occurrences of Events in DNA Sequences
Author Information
Author(s): Haiminen Niina, Mannila Heikki, Terzi Evimaria
Primary Institution: University of Helsinki
Hypothesis
Can we determine the significance of co-occurrences of transcription factor binding sites in bursty DNA sequences using different null models?
Conclusion
More sophisticated null models provide better results for identifying significant co-occurrences in bursty data compared to simple models.
Supporting Evidence
- The study shows that simple null models yield many false positives in bursty data.
- More sophisticated models accurately identify significant co-occurrences in synthetic data.
- The effect of window size on significance results was demonstrated.
Takeaway
This study looks at how often certain DNA events happen together and finds that using better models helps us understand these patterns more accurately.
Methodology
The study evaluates different null models for co-occurrence significance using synthetic and real data of transcription factor binding sites.
Potential Biases
Potential biases may arise from the choice of null models and the specific datasets used.
Limitations
The study may not account for all biological complexities and variations in DNA sequences.
Statistical Information
P-Value
p ≤ 0.01
Statistical Significance
p<0.01
Digital Object Identifier (DOI)
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