20.500.12556/DKUM-91573 Diferencialno izražanje genov in učinek filtriranja nizko izraženih genov pri analizi RNA sekvenciranja Differential gene expression and the effect of low gene expression filtering in RNA sequencing analysis Uvod: Sekvenciranje RNA (analiza RNA-seq) se sooča z izzivi obdelave podatkov in razvojem metod za učinkovito shranjevanje, pridobivanje in obdelavo velikih količin podatkov z namenom, da se zmanjša število napak določevanja nukleotidnega zaporedja med drugim tudi na način z odstranitvijo odčitkov nižje kakovosti. Metode: S pomočjo programskega orodja R smo iz treh različnih podatkovnih baz za tri različne bolezni (Crohnova bolezen, astma, miomi maternice) izvedli RNA-seq analizo v katero smo vključili filtriranje nizko izraženih z metodo CPM, kjer smo določili prag filtriranja nizko izraženih genov na podlagi statističnega izračuna minimuma, maksimuma in povprečja izražanja genov. Rezultati: V okviru naloge smo ugotovili, da različni pragi filtriranja ne spremenijo števila nabora genov v končnih rezultatih analize RNA-seq. Pri vplivu postavitve različnih pragov filtriranja na nabor prvih 20 najbolj statistično značilno diferencialno izraženih genov je bila izrazita razlika med različno zastavljenimi pragi filtriranja samo v primeru Crohnove bolezni. Pri testiranju, ali se izločeni geni pri danem pragu filtriranja pojavijo kot statistično značilno diferencialno izraženi geni v analizi brez filtriranja, smo ugotovili, da se velik delež izločenih genov, še posebej pri nižjih pragovih filtriranja, še vedno pojavi kot statistično značilen v analizi brez filtriranja. Razprava in sklep: Na podlagi rezultatov smo ugotovili, da postavitev različnih pragov filtriranja nima posebnega učinka na rezultate diferencialnega izražanja genov. Introduction: RNA-seq analysis faces challenges in data processing and the development of methods for efficient storage, retrieval, and processing of large amounts of data, with the aim of reducing the number of errors in determining the nucleotide sequence, among other objectives, by removing lower-quality reads. In this thesis we used a CPM method to eliminate lower-quality reads, determining the threshold for filtering low-expressed genes based on statistically calculated minimum, maximum, and average gene expression. Methods: Using the R programming tool, we conducted an RNA-seq analysis from three different databases, incorporating the filtering of low-expressed genes through the CPM method. Results: As part of the task, we found that varying filtering thresholds did not alter the number of gene sets in the final results of the RNA-seq analysis. When assessing the impact of different filtering thresholds on the set of the top 20 statistically significant differentially expressed genes, a notable difference was observed only in the case of Crohn's disease. In testing whether genes excluded at a given filtering threshold appear as statistically significant differentially expressed genes in the analysis without filtering, we found that a large proportion of excluded genes, particularly at lower filtering thresholds, still appear as statistically significant in the unfiltered analysis. Discussion and conclusion: Based on the results, we found that the placement of different filtering thresholds does not have a significant impact on the results of differential gene expression. genska ekspresija astma Crohnova bolezen miomi maternice gene expression asthma Crohn’s disease uterine leiomyomas true true false [Š. Fabčič] Slovenski jezik Angleški jezik Magistrsko delo/naloga 2025-01-16 08:39:16 2025-05-06 09:01:52 2025-05-07 03:09:53 0000-00-00 00:00:00 2025 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 575.1+57.088.7(043.2) 232133123 MAG_Fabcic_Spela_2025.pdf MAG_Fabcic_Spela_2025.pdf 1 9F27A4F90D10F951E168ABC1A1EBDFAC 7c441ca81038674c97c06baf083c4bf62f787108d5dbaed7b39fcd081712ae85 84ea4ec1-d3de-11ef-8ff8-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=187887 Fakulteta za zdravstvene vede 0 0 0