dc.creator | Anđelković, Marina | |
dc.creator | Skakić, Anita | |
dc.creator | Stevanović, Nina | |
dc.creator | Parezanović, Marina | |
dc.creator | Komazec, Jovana | |
dc.creator | Klaassen, Kristel | |
dc.creator | Spasovski, Vesna | |
dc.creator | Stojiljković, Maja | |
dc.creator | Pavlović, Sonja | |
dc.date.accessioned | 2023-06-06T08:41:55Z | |
dc.date.available | 2023-06-06T08:41:55Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 2566-2937 | |
dc.identifier.issn | 2566-431X (Online) | |
dc.identifier.issn | | |
dc.identifier.uri | https://imagine.imgge.bg.ac.rs/handle/123456789/1900 | |
dc.description.abstract | Rare lung diseases (RLDs) are a group of diseases that individually affect one in 2,000 people, with an
estimate that about 80% of RLDs have a genetic origin. Despite the variations among RLDs in clinical
characteristics and manifestations, most of these diseases similarly damage the lungs, making diagnosis
difficult. The utility of NGS technology in RLDs for diagnostic purposes allows a better understanding
of the genetic background, however, the identification and classification of disease-causing variants are
challenging. Further, numerous VUS (variants of uncertain significance) that cannot be precisely
defined and classified are produced. The main goal of this study was to create a unique guideline that
will enable the standardization of the assessment of novel genetic variants in RLDs causative genes.
The designed pipeline consists of three main steps: (1) sequencing, detection, and identification of
genes/variants, (2) classification of variants, and (3) characterization of variants using in silico
structural and functional analysis. The pipeline validation was performed through the analysis of
variants detected in a disease-causing and candidate genes of one of the RLDSs, and detected VUS
variants have gained diagnostic significance. The application of this pipeline resulted in the
identification and classification of novel variants, through analysis at the transcriptional, translational,
and posttranslational levels, and led to accurate diagnosis. | sr |
dc.language.iso | en | sr |
dc.publisher | Sarajevo : Institute for Genetic Engineering and Biotechnology, University of Sarajevo | sr |
dc.rights | openAccess | sr |
dc.source | Genetics & Applications | sr |
dc.subject | pipeline | sr |
dc.subject | rare lung diseases (RLDs) | sr |
dc.subject | classification of variants | sr |
dc.subject | characterization of variants | sr |
dc.subject | sequencing | sr |
dc.subject | detection | sr |
dc.subject | identification of genes/variants | sr |
dc.title | Improving the diagnostics of rare lung disorders using a uniquely designed pipeline for analysis of ngs data | sr |
dc.type | conferenceObject | sr |
dc.rights.license | ARR | sr |
dc.citation.issue | 2 (Special edition) | |
dc.citation.spage | 104 | |
dc.citation.volume | 7 | |
dc.description.other | Book of abstracts: International Conference of Biochemists and Molecular Biologists in Bosnia and Herzegovina - ABMBBIH May, 2023 | sr |
dc.identifier.fulltext | https://imagine.imgge.bg.ac.rs/bitstream/id/229214/BookOfAbstracts_1-5,122.pdf | |
dc.identifier.rcub | https://hdl.handle.net/21.15107/rcub_imagine_1900 | |
dc.type.version | publishedVersion | sr |