Primerjava pristopov edgeR in voom za analizo diferencialnega izražanja genov na podlagi podatkov sekvenciranja transkriptoma

Bezjak, Lara

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Title:	Primerjava pristopov edgeR in voom za analizo diferencialnega izražanja genov na podlagi podatkov sekvenciranja transkriptoma
Authors:	ID Bezjak, Lara (Author) ID Potočnik, Uroš (Mentor) More about this mentor... ID Gorenjak, Mario (Comentor)
Files:	MAG_Bezjak_Lara_2019.pdf (1,59 MB) MD5: D8064F2F2BB3C02227F502F6DFB7A483 PID: 20.500.12556/dkum/7208b151-3ded-49e0-8933-695e0158e81f
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FZV - Faculty of Health Sciences
Abstract:	Izhodišče: Z razvojem visoko zmogljivih tehnologij sekvenciranja, ki so omogočile pridobitev velike količine podatkov iz bioloških vzorcev, je hitro naraslo tudi število programskih orodij za urejanje teh podatkov, vendar pa trenutno še ni soglasja o najprimernejšem postopku ali metodi za identifikacijo različno izraženih genov s tehnologijo sekvenciranja naslednje generacije (RNA-seq). Namen naloge je bil analizirati dva pristopa za analizo RNA-seq podatkov in njune rezultate validirati z zlatim standardom. Metode: V nalogi smo uporabili dva pristopa, edgeR (Robinson, et al., 2010) in limma (Ritchie, et al., 2015) -voom (Law, et al., 2014), ter njune rezultate preverili z metodo RT-qPCR. Z RT-qPCR smo preverili štiri gene, ki so imeli izračunane nasprotujoče si log2FC in p-vrednosti. Na koncu smo zbrane rezultate vseh treh metod analizirali s programskim orodjem SPSS. Rezultati: Rezultati Spearmanovega testa korelacije so pokazali močno korelacijo med izračunanimi log2FC in p-vrednostmi obeh pristopov, vendar je Wilcoxonov test pokazal, da se log2FC in p-vrednosti kljub temu statistično značilno razlikujejo glede na to, katero metodo smo uporabili. Tri gene, ki so se po metodah edgeR in voom najbolj razlikovali, smo analizirali z RT-qPCR in ugotovili, da dobljeni rezultati qRT-PCR bolj sovpadajo s pristopom voom kot z edgeR, kar je potrdil tudi Spearmanov test korelacije in Wilcoxonov test. Diskusija: Iz rezultatov smo zaključili, da je pristop voom primernejši, saj daje zanesljivejše rezultate kot edgeR kljub temu da smo imeli zelo majhen vzorec (3 posameznike za vsako skupino).
Keywords:	RNA sekvenciranje, transkriptomika, R, RT-qPCR, bioinformatika
Place of publishing:	Maribor
Publisher:	[L. Bezjak]
Year of publishing:	2019
PID:	20.500.12556/DKUM-74501
UDC:	575.112(043.2)
COBISS.SI-ID:	2542756
NUK URN:	URN:SI:UM:DK:2OPQN9EI
Publication date in DKUM:	11.11.2019
Views:	1673
Downloads:	248
Metadata:
Categories:	FZV
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Licences

License:	CC BY-ND 4.0, Creative Commons Attribution-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nd/4.0/
Description:	Under the NoDerivatives Creative Commons license one can take a work released under this license and re-distribute it, but it cannot be shared with others in adapted form, and credit must be provided to the author.
Licensing start date:	29.08.2019

Secondary language

Language:	English
Title:	Comparison of edger and voom approaches for differential expression analysis based on transcriptome sequencing data
Abstract:	Introduction: With the development of high-end sequencing technologies, that produce large amounts of data from biological samples, the number of software tools for analyzing this data has also rapidly increased, but there is no agreement on the most appropriate approach for identifying differentially expressed genes. The purpose of this master's thesis was to analyze two approaches for the RNA-seq data analysis and validated their results with the gold standard. Methods: Here, we compare two approaches, edgeR (Robinson, et al., 2010) and limma (Ritchie, et al., 2015) -voom (Law, et al., 2014), and we verified their results using the RT-qPCR method. Using RT-qPCR, we verified four genes that had differently computed log2FC and p-values. Finally, the results of all three methods were analyzed with the SPSS software tool. Results: The results of the Spearman's rank-order correlation showed a strong correlation between calculated log2FC and p-values of both approaches, but the Wilcoxon’s test showed that the values were significantly differ. Among the four selected genes, only three were analyzed with RT-qPCR, since the primers for one gene were not specific enough. Obtained results were more matched with the voom approach than with the edgeR, which was also confirmed by Spearman's correlation and the Wilcoxon signed-rank test. Discussion: From the results we concluded that the voom approach is better, since it gives more reliable results, even though we had a very small sample size (3 individuals for each group).
Keywords:	RNA sequencing, Transcriptomics, R, RT-qPCR, Bioinformatics

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