COMIT: A Tool for Identifying Noncoding Motifs in Coding Sequences
Author Information
Author(s): Kural Deniz, Ding Yang, Wu Jiantao, Korpi Alicia M, Chuang Jeffrey H
Primary Institution: Department of Biology, Boston College
Hypothesis
Can the COMIT algorithm effectively identify functional noncoding motifs in coding sequences?
Conclusion
The COMIT algorithm successfully identifies numerous noncoding motifs under natural selection in coding sequences.
Supporting Evidence
- COMIT identified 503 motifs with a z-score > 15, indicating strong noncoding pressures.
- The algorithm shows a clear correlation between COMIT scores and experimental data for splicing enhancers.
- COMIT scores are robust across different mammalian lineages, suggesting conserved functional motifs.
Takeaway
The COMIT tool helps scientists find important hidden signals in DNA that don't code for proteins but still play crucial roles.
Methodology
The COMIT algorithm calculates z-scores of sequence conservation for motifs, correcting for amino acid sequences and addressing the variable codon frame problem.
Potential Biases
Potential biases from unaccounted dinucleotide effects and the influence of amino acid sequences on conservation scores.
Limitations
The algorithm may not detect all nucleotide-level selection due to its specific null model assumptions.
Statistical Information
P-Value
<0.00001
Statistical Significance
p<0.00001
Digital Object Identifier (DOI)
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