Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples
| dc.contributor.author | Sun, Lillian | |
| dc.contributor.author | Namboodiri, Surya | |
| dc.contributor.author | Chen, Emily | |
| dc.contributor.author | Sun, Shuying | |
| dc.date.accessioned | 2020-03-11T13:15:28Z | |
| dc.date.available | 2020-03-11T13:15:28Z | |
| dc.date.issued | 2019-01 | |
| dc.description.abstract | DNA methylation plays a significant role in regulating the expression of certain genes in both cancerous and normal breast tissues. It is therefore important to study within-sample co-methylation, ie, methylation patterns between consecutive sites in a chromosome. In this article, we develop 2 new methods to compare co-methylation patterns between normal and cancerous breast samples. In particular, we investigate the co-methylation patterns of 4 different methylation states/levels separately. Using these 2 methods, we focus on addressing the following questions: How often does 1 methylation state change to other methylation states and how is this change dependent on chromosome distance? What co-methylation patterns do normal and cancerous breast samples have? Do genomic sites with different methylation states/levels have different co-methylation patterns? Our results show that cancerous and normal co-methylation patterns are significantly different. We find that this difference exists even when the physical distance of 2 sites are less than 50 bases. Breast cancer cell lines tend to remain in the same methylation state more often than normal samples, especially for the no/low or high/full methylation states. We also find that the co-methylation region lengths for various methylation states (no/low, partial, and high/full methylation states) are very different. For example, the co-methylation region lengths for partial methylation regions are shorter than the unmethylated or fully methylated regions. Our research may provide a deep understanding of co-methylation patterns. These co-methylation patterns will aid in discovering and understanding new methylation events that may be related to novel biomarkers. | |
| dc.description.department | Mathematics | |
| dc.format | Text | |
| dc.format.extent | 14 pages | |
| dc.format.medium | 1 file (.pdf) | |
| dc.identifier.citation | Sun, L., Namboodiri, S., Chen, E., & Sun, S. (2019). Preliminary analysis of within-sample co-methylation patterns in normal and cancerous breast samples. Cancer Informatics, 18, pp. 1-14. | |
| dc.identifier.doi | https://doi.org/10.1177/1176935119880516 | |
| dc.identifier.issn | 1176-9351 | |
| dc.identifier.uri | https://hdl.handle.net/10877/9371 | |
| dc.language.iso | en | |
| dc.publisher | Sage | |
| dc.rights.holder | © 2019 The Author(s). | |
| dc.rights.license | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. | |
| dc.source | Cancer Informatics, 2019, Vol. 18, pp. 1-14. | |
| dc.subject | bioinformatics | |
| dc.subject | breast cancer | |
| dc.subject | within sample co-methylation | |
| dc.subject | Mathematics | |
| dc.title | Preliminary Analysis of Within-Sample Co-methylation Patterns in Normal and Cancerous Breast Samples | |
| dc.type | Article |