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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/3920

Title: Fragment based immunoglobulin and T cell receptor identification and its applications
Authors: Zhang, Bochao
Keywords: Biomedical engineering;T cells--Receptors;Immunoglobulins
Issue Date: Jun-2012
Abstract: In my thesis I have created novel methodologies for the identification of germline V genes from limited sequence data. To do so I have used a ‘dictionary’ of sequence fragments derived from the IMGT database of germline immunoglobulin (Ig) and T cell receptor (TCR) genes. Each of these sequence fragments was identified as being unique to single V gene fragment and a single position amongst all V, D and J genes in the database. Thus fitting to these fragments could identify both the germline origin of queried V gene fragments and their alignment. Such an application is essential for many further studies. Repertoire diversity is an important factor in the progression of the immune response. In studies of inflammation, in reaction to disease, in autoimmunity and in cancer, we need to characterize repertoire diversity. To do so we first need to separate the sequences into clones and associate them with their germline ancestors. There are several extant tools to deal with small amount of sequences. However, such experiments do not usually have enough coverage of the repertoire for proper analysis. High throughput sequencing can produce millions of sequences at a low cost, giving us substantial snapshots of the repertoire. However this technology suffers from two main issues: it generates short, partial sequences of the Ig genes and has an intrinsic error rate. These make the identification using conventional methods untenable. We here present a novel method that can associate the V genes of Ig and TCR nucleotide sequences with their appropriate germlines with high accuracy and known precision. Allowing for the essential first step in any computational processing of high throughput Ig and TCR sequencing data.
Description: Thesis (M.S., Biomedical engineering)--Drexel University, 2012.
URI: http://hdl.handle.net/1860/3920
Appears in Collections:Drexel Theses and Dissertations

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