| dc.description.abstract |
<p>As fundamental structural units of the chromatin, nucleosomes are involved in virtually
all aspects of genome function. Different methods have been developed to map genome-wide
nucleosome positions, including MNase-seq and a recent chemical method requiring genetically
engineered cells. However, these methods are either low resolution and prone to enzymatic
sequence bias or require genetically modified cells. The DNase I enzyme has been used
to probe nucleosome structure since the 1960s, but in the current high throughput
sequencing era, DNase-seq has mainly been used to study regulatory sequences known
as DNase hypersensitive sites. This thesis shows that DNase-seq data is also very
informative about nucleosome positioning. The distinctive oscillatory DNase I cutting
patterns on nucleosomal DNA are shown and discussed. Based on these patterns, a Bayes
factor is proposed to be used for distinguishing nucleosomal and non-nucleosomal genome
positions. The results show that this approach is highly sensitive and specific. A
Bayesian method that simulates the data generation process and can provide more interpretable
results is further developed based on the Bayes factor investigations. Preliminary
results on a test genomic region show that the Bayesian model works well in identifying
nucleosome positioning. Estimated posterior distributions also agree with some known
biological observations from external data. Taken together, methods developed in this
thesis show that DNase-seq can be used to identify nucleosome positioning, adding
great value to this widely utilized protocol.</p>
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