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Computational identification and characterization of genotype-phenotype associations
The adaptive immune system is essential in defending the host against diverse and rapidly evolving pathogens, or controlling diseases such as cancer. To perform its duty, the adaptive immunity depends on enormously diverse repertoires of B- and T-cell receptors (BCRs and TCRs). In light of the rapid advancement in high-throughput sequencing (HTSeq) technologies, it is now possible to study the properties of these repertoires, which is central to the development of vaccines, new prognostic markers, and treatments for cancer and autoimmune diseases. One challenge in extracting biologically meaningful information from HTSeq data comes from the fact that this data is both complex and massive. We can anticipate that additional improvements in HTSeq technologies will generate even larger datasets with hundreds of millions of sequenced reads from potentially hundreds or thousands of individuals. To meet these challenges, we need new computational methods. Furthermore, the biological processes that contribute to the diversity of BCR repertoires are stochastic in nature. This calls for the use of probabilistic modeling to accurately describe these processes. I begin this thesis with an introduction of the most relevant concepts of B-cell mediated immunity (chapter 1). This is followed by general introduction of probabilistic modeling for Bayes inference (chapter 2). The main result of this thesis are computational methods, which are summarized in two publications (chapter 3). In the first publication (section 3.1), I introduce IgGeneUsage, a computational tool for probabilistic detection of differential Ig gene usage under different biological conditions (e.g. infected vs. healthy subjects). We know that V(D)J recombination of different germline-encoded Ig genes is an important component that contributes to the enormous diversity of BCR repertoires. Detection of disrupted usage of Ig genes has previously been reported e.g. in chronic lymphocytic leukemia, where specific Ig gene disruptions may be used as prognostic ...
Computational identification and characterization of genotype-phenotype associations
The adaptive immune system is essential in defending the host against diverse and rapidly evolving pathogens, or controlling diseases such as cancer. To perform its duty, the adaptive immunity depends on enormously diverse repertoires of B- and T-cell receptors (BCRs and TCRs). In light of the rapid advancement in high-throughput sequencing (HTSeq) technologies, it is now possible to study the properties of these repertoires, which is central to the development of vaccines, new prognostic markers, and treatments for cancer and autoimmune diseases. One challenge in extracting biologically meaningful information from HTSeq data comes from the fact that this data is both complex and massive. We can anticipate that additional improvements in HTSeq technologies will generate even larger datasets with hundreds of millions of sequenced reads from potentially hundreds or thousands of individuals. To meet these challenges, we need new computational methods. Furthermore, the biological processes that contribute to the diversity of BCR repertoires are stochastic in nature. This calls for the use of probabilistic modeling to accurately describe these processes. I begin this thesis with an introduction of the most relevant concepts of B-cell mediated immunity (chapter 1). This is followed by general introduction of probabilistic modeling for Bayes inference (chapter 2). The main result of this thesis are computational methods, which are summarized in two publications (chapter 3). In the first publication (section 3.1), I introduce IgGeneUsage, a computational tool for probabilistic detection of differential Ig gene usage under different biological conditions (e.g. infected vs. healthy subjects). We know that V(D)J recombination of different germline-encoded Ig genes is an important component that contributes to the enormous diversity of BCR repertoires. Detection of disrupted usage of Ig genes has previously been reported e.g. in chronic lymphocytic leukemia, where specific Ig gene disruptions may be used as prognostic ...
Computational identification and characterization of genotype-phenotype associations
Kitanovski, Simo (Autor:in) / Hoffmann, Daniel
23.03.2021
Hochschulschrift
Elektronische Ressource
Englisch
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