Your browser does not support JavaScript!

Home    Collections    Type of Work    Post-graduate theses  

Post-graduate theses

Search command : Author="Μαυρομούστακου"  And Author="Ήβη"

Current Record: 11 of 6547

Back to Results Previous page
Next page
Add to Basket
[Add to Basket]
Identifier 000464362
Title A scalable and reproducible bioinformatics workflow for HLA type inference from NGS data
Alternative Title Μια κλιμακούμενη και αναπαραγώγιμη ροή βιοπληροφορικής εργασίαέυρεσης τύπων HLA από δεδομένα αλληλούχισης επόμενης γενιάς
Author Κολιαδήμα, Μαρία-Ευτυχία
Thesis advisor Καντεράκης, Αλέξανδρος
Reviewer Λατσούδη, Λένα
Ποταμιάς, Γεώργιος
Abstract Human Leukocyte Antigen (HLA) group of genes is one of the most polymorphic regions in the human genome with significant roles in antigen presentation (donor-recipient compatibility during hematopoietic stem cell transplantation-HSCT) adaptive immune responses underlying disease susceptibility (immunological & metabolic diseases and cancer) and drug response (pharmacogenetics). Also, the high allelic diversity and significant linkage disequilibrium (LD) of HLA have proven useful for singling out individuals and populations, since certain alleles show distinctive profiles in populations. Thus, HLA is important in studying the origins and genetic structure of human groups, as well as inferring relations between populations and ethnic groups. Even though sequence-based typing (SBT) is the gold standard method for HLA typing, the advancement of sequencing technologies has resulted in the growing need to use Next Generation Sequencing (NGS) for accurate HLA calling. However, the high allelic and structural variation, inter-gene sequence homologies and high LD make HLA analysis challenging. Recent advanced algorithmic approaches including accurate SNP-based HLA imputation and HLA genome inference from whole exome and genome sequencing (WES and WGS) data, have rendered the HLA region significantly accessible. The result has been an explosion of in-silico NGS-based HLA typing software solutions, each using different methods for imputation or inference. Despite the continued growth in this bioinformatics field, a single workflow has not been developed enabling the concomitant evaluation of the HLA typed alleles. In these thesis we compiled 4 open-source genome inference algorithms (HLA*LA, HISAT-Genotype, HLA-HD and HLAScan) able to call 2nd-field alleles for Class I (HLA-A, -B, -C) and Class II genes (HLA-DRB1, -DQB1) using Illumina short read NGS data.
Language English
Issue date 2024-04-17
Collection   School/Department--School of Medicine--Department of Medicine--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/f/6/6/metadata-dlib-1714027370-402539-17539.tkl Bookmark and Share
Views 3

Digital Documents
No preview available

No permission to view document.
It won't be available until: 2027-04-17