Phylogenetic fatemapping: estimating allelic dropout probability in single cell genomic sequencing
Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Single-cell genomic sequencing is a rapidly developing field that will play a vital role in human biology and science in the future. As of now, next-generation sequencing is accelerating in speed and decreasing in cost more quickly than Moore's law. Studies have shown that all cells in the human body have with very high probability a unique genomic signature, due to the somatic evolution which have accumulated mutations starting from the zygotic state. The possible reconstruction of phylogenetic lineage trees would be of vital importance to several fields in medicine, such as the stem cell research field. However, state-of-the-art methods for amplification such as WGA currently suffers from extensive allelic dropout which is troublesome when reconstructing phylogenetic trees. We have constructed a statistical model that can be used to predict site specific allelic dropout. Our results suggests that logistic regression is a suitable method for modelling allelic dropout, and that there is a non-linear relationship between the read depth and distance.
Place, publisher, year, edition, pages
IdentifiersURN: urn:nbn:se:kth:diva-186453OAI: oai:DiVA.org:kth-186453DiVA: diva2:927344
Subject / course
Bachelor of Science in Engineering - Computer Engineering