The advent of the high-throughput sequencing (HTS) technology has greatly accelerated research in life sciences. Due to its low cost and high efficiency, it is nowadays commonly used to answer various biological questions. In general, in HTS, the sequence of millions of DNA fragments is determined in parallel and these fragments can in turn be generated using different sequencing methods. With the rapid advancement of HTS technologies, their applications seem almost endless, for example it is

more »

... w possible to sequence an entire genome in less than one day. Besides whole genome sequencing, HTS has various other applications like targeted resequencing, quantification of gene expression profiles (RNA-seq) and genome-wide identification of protein-DNA interactions such as transcription factor binding sites or chromatin histone marks (ChIP-seq). However, the analysis of the massive datasets generated by HTS is only possible with sophisticated bioinformatics methods. In this thesis, I have presented computational approaches for analyzing data obtained by targeted DNA resequencing, RNA-seq and ChIP-seq, aimed at answering biological questions regarding cardiac disease and skeletal muscle development. First, a novel copy number variation (CNV) calling method was developed to identify individual disease-relevant CNVs using exome or targeted resequencing data of small sets of samples. Detecting CNVs from targeted resequencing data is difficult due to non-uniform read-depth between captured regions. Moreover, a method was needed to detect personalized CNVs from small cohort of patients without using controls. Thus, we developed such a method and evaluated it using publicly available data of eight HapMap samples, and subsequently applied it to a small number of Tetralogy of Fallot (TOF) patients. In addition to our method, we used the two publicly available tools, namely ExomeDepth and CoNIFER. ExomeDepth identified more CNVs for HapMap samples as compared to CoNIFER and our method; however, the positive predictive value was [...]