Two algorithmic problems in analyzing genetic and epigenetic variations

Abstract

Single nucleotide polymorphism (SNP) is the most common type of genetic variations.Accurate detection of SNPs is crucial to many downstream studies. To detect SNPs,

MALDI-TOF mass spectrometry combined with base-specific cleavage reactions has been employed in many experiments. A new SNP detecting algorithm is presented in the thesis, together with the performance evaluation of its implemented program called SnpMs.Results demonstrate that SnpMs has a high ability to detect SNP mutations accurately. Cytosine methylation plays an important role in many biological regulation processes. The current golden standard method for analyzing cytosine methylation is BS-Seq. In this thesis, a new tool called TAMeBS is introduced to align BS-Seq reads and estimate the methylation status of each cytosine. Experimental results on both simulated and real data showed that TAMeBS could detect many more uniquely best mapped reads while achieving a good balance between sensitivity and precision.