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Identification of Alternative Splicing and RNA Editing Events in Invasive Breast Carcinoma Open Access

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There has been considerable effort to predict alternative splicing and RNA-editing sites in exome and transcriptome sequences using various tools in computational biology and bioinformatics. With the current advancements in the field and the emergence of various modules and computer languages, there are multiple tools claiming to produce sufficient algorithms to predict sites of splicing and RNA-editing in individual samples, but as the field progresses, the definition of precision gets more complex and so too do the algorithms and number of samples needed in order to give precise predictions for these events. Although many of these tools have been quite successful in predicting these events, there remain some missing pieces at these sites including site coherence and concurrent specificity especially among larger sample sets. Working with Dr. Anelia Horvath, I am developing two sets of software, SNPlice and RNA-2-DNA aligner, to estimate alternative splicing and RNA editing events throughout several transcriptome and exome datasets simultaneously. Importantly, these two programs are designed to evaluate highly probabilistic novel events coherently using unique junction files that belong to a specific sample as a template and estimate such events prospectively across the sample sets. These tools are being developed through the Python pysam module. We are validating the predicted sites with follow-up in vitro experimentation. We are working with thirty breast carcinoma tissue samples and thirty concordant normal tissue samples in our analysis pipeline. Drawing on this significant number of samples will prove to be a great asset for the scientific community studying breast cancer in that our analyses will generate a potential list of relevant polymorphic sites predicted to either undergo alternative splicing or RNA-editing. Given the association of these events in the differentiation and development of cancer, my thesis will help guide understanding of the specific molecular mechanisms involved in the onset and persistence of invasive breast cancer.

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