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dc.contributor.advisor Nakhleh, Luay K.
dc.creatorZafar, Hamim
dc.date.accessioned 2016-01-27T19:37:36Z
dc.date.available 2016-01-27T19:37:36Z
dc.date.created 2015-05
dc.date.issued 2015-04-23
dc.date.submitted May 2015
dc.identifier.citation Zafar, Hamim. "A SNP Calling And Genotyping Method For Single-cell Sequencing Data." (2015) Master’s Thesis, Rice University. https://hdl.handle.net/1911/88187.
dc.identifier.urihttps://hdl.handle.net/1911/88187
dc.description.abstract In this thesis, we propose a single nucleotide polymorphism (SNP) calling and genotyping algorithm for single-cell sequencing data generated by the recently developed single-cell sequencing (SCS) technologies. SCS methods promise to address several key issues in cancer research which previously could not be resolved with data obtained from second generation or next-generation sequencing (NGS) technologies. SCS has the power to resolve cancer genome at a single-cell level and can characterize the genomic alterations that might differ from one cell to another. SNPs are the most commonly occurring genomic variations that alter the gene functions in cancer. Several methods exist for calling SNPs from NGS data. However, these methods are not suitable in the SCS scenario because they do not account for the various amplification errors associated with the SCS data. As a result, the existing SNP calling methods perform poorly, producing a large number of false positives when applied on SCS data. To the best of our knowledge, no SNP calling method exists that is specifically designed for SCS data. Our SNP calling algorithm is specifically designed for SCS data and the underlying statistical model deals with the inherent errors of SCS like allelic dropout, high bias for C : G > T : A and other amplification errors. This results in ~50% reduction in the number of false positives and ~30% increase in precision in calling SNPs as compared to GATK, a state-of-the-art SNP calling method for NGS data. Our algorithm also employs an improved genotyping method to properly genotype the individual cells by avoiding the sequencing errors (e.g., base calling error). Our method is the first SCS-specific SNP calling method and it can be used to characterize the SNPs present in individual cancer cells. Potentially, it can be applied as a first step in the genealogical analysis of tumor cells for tracing the evolutionary history of a tumor.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectSingle Nucleotide Polymorphism
SNP calling
Genotyping
Single Cell sequencing
Algorithm
dc.title A SNP Calling And Genotyping Method For Single-cell Sequencing Data
dc.contributor.committeeMember Kavraki, Lydia E
dc.contributor.committeeMember Jermaine, Chris M
dc.contributor.committeeMember Chen, Ken
dc.date.updated 2016-01-27T19:37:36Z
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Computer Science
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Science


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