- Deep Genomic Analysis of Tumor Specimens
- Project Year:
2020
- REU Student (s):
Timothy Hedspeth | Emmanuel College MA
- Student 1 Institution:
Emmanuel College
- Project Mentor:
Hossein Khiabanian
- Project Mentor Area:
Rutgers Cancer Institute of New Jersey
- Project Abstract:
Single cell sequencing is a new field in biology that allows for the extraction of tumor cell populations, and subsequent analysis on this data leads to a better understanding of the differences in cells from these populations. The data in regard to reads and mutant allele coverage is critical to understanding how phenotype of cells are informed. Data extracted from thousands of cells yielded wide ranges of depth of UMI (Unique Molecular Identifier) and mutant UMI reads for single cells and base pairs. The analysis showed similar patterns of depth between the genes studied with low mutant coverage, which is not unexpected with single cell data. The results of having low data coverage results in less statistical power when trying to create confidence intervals for variant allele frequency. Further analysis using known mutation data showed that a previously developed probability function can result in a negative value when variant allele frequency is greater than .5. Thus, future directions of this project will focus on a development of a probability model based on our data.
