20.500.12556/RUL-149788 Določanje podtipov limfocitov T na osnovi podatkov sekvenciranja RNA posameznih celic Identification of T lymphocyte subtypes from single-cell RNA sequencing DATA Določevanje limfocitov T je z razvojem scRNA-seq dobilo nov vpogled v heterogeno sestavo limfocitov T. Pri limfocitih T poznamo več podtipov, ki imajo vsak svojo funkcijo. Iz sestave limfocitov T se lahko razbere bolezensko stanje pacienta. To je uporabno predvsem pri določevanju rakavih obolenj in pri kroničnih okužbah. scRNA-seq je relativno nova tehnologija, zato je še v procesu izpopolnjevanja. Tehnologija scRNA-seq nam omogoča opazovanje transkriptoma posameznih celic v vzorcu. Za izvedbo scRNA-seq so razvili različne protokole. Izziv pri scRNA-seq je velika količina podatkov, ki jih moramo analizirati, kar zahteva visoko računalniško zmogljivost. Na voljo imamo različna programska orodja za analizo. Analiza podatkov se začne s predobdelavo podatkov, pri čemer opravimo kontrolo kakovosti transkriptov in odpravimo neustrezne celice. Temu sledi kvantitativna analiza transkriptoma in kartiranje na referenčni genom. Po predobdelavi podatkov se lahko lotimo analize in vizualizacije podatkov. Opravljene študije so do zdaj dokazale, da s scRNA-seq pri limfocitih T odkrijemo večjo heterogenost podtipov v primerjavi s tradicionalnimi metodami. The advancement of scRNA-seq has brought new insights into the heterogeneous composition of T lymphocytes. Within T lymphocytes, several subtypes are known, each having its specific function. The composition of T lymphocytes can provide insights into a patient's disease state, particularly in the determination of cancerous conditions and chronic infections. scRNA-seq is a relatively novel technology and is still in the process of refinement. This technology allows us to observe the transcriptome of individual cells in a sample. Various protocols for conducting scRNA-seq have been developed. An inherent challenge in scRNA-seq is the substantial amount of data that needs to be analyzed, demanding high computational capacity. Different software tools are available for analysis. Data analysis begins with data preprocessing, including transcript quality control and the removal of unsuitable cells. Subsequently, quantitative transcriptomic analysis and mapping to a reference atlas are performed. Following data preprocessing, we can engage in data analysis and visualization to derive meaningful insights. Completed studies have demonstrated that scRNA-seq in T lymphocytes reveals a diverse heterogeneity of subtypes compared to traditional methods. scRNA-seq transkriptom limfociti T anotacija celic scRNA-seq transcriptome cell annotation lymphocytes T true false false Slovenski jezik Angleški jezik Diplomsko delo/naloga 2023-09-10 07:17:00 2023-09-10 07:17:02 2023-10-05 12:48:46 0000-00-00 00:00:00 2023 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 228943 164321539 35142.pdf 35142.pdf 1 DEA2936623F30A42A6F60ADE77D70D36 21fe39200eb2fda832d933fe15e6b38e00b0a88b6405514156d41ac94637fa0d 46802c19-4f99-11ee-a2ce-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=174292 Biotehniška fakulteta 0 0 0