Primerjava  bioinformatskih orodij  za anotacijo podatkov  eksoma pridobljenih z  dna sekvenciranjem  naslednje generacije

Toplak, Miklavž

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Title:	Primerjava bioinformatskih orodij za anotacijo podatkov eksoma pridobljenih z dna sekvenciranjem naslednje generacije
Authors:	ID Toplak, Miklavž (Author) ID Gorenjak, Mario (Mentor) More about this mentor... ID Potočnik, Uroš (Comentor)
Files:	MAG_Toplak_Miklavz_2021.pdf (7,93 MB) MD5: E72C3891AF9D41EE5CE6E74B8AF02A4E PID: 20.500.12556/dkum/4d0b72e7-e85e-4f7f-9eb6-4ac5bfa2d418
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FZV - Faculty of Health Sciences
Abstract:	Uvod: Genomska anotacija je ključen korak po sekvenciranju DNA, saj nam pomaga identificirati ključne funkcionalne elemente nukleotidnega zaporedja ter nam s tem priskrbi pomen nukleotidnega zaporedja, ki nas zanima. Eksom je definiran kot nukleotidno zaporedje, ki obsega vse eksome vseh genov, ki kodirajo proteine v genomu. Eksom predstavlja med 1 in 2 % celotnega genoma, vsebuje pa kar 85 % znanih različic, ki povzročajo bolezni. Metode: V empiričnem delu naloge smo v začetku zbrali vsa izbrana orodja za anotacijo in jih naložili na naš namizni računalnik, nato pa smo z vsakim od orodij izvedli anotacijo na podatkih pridobljenih v laboratoriju Centra za humano molekularno genetiko in farmakogenomiko Medicinske fakultete Univerze v Mariboru s sekvenciranjem naslednje generacije DNA izoliranih iz 24 bolnikov. Podatke sekvenciranja eksoma v VCF formatu smo analiziraliz bioinformatskimi orodji ANNOVAR, Exomiser, VarAFT, SnpEff in Ensembl VEP. Vsa orodja z izjemo VarAFT so orodja, ki se zaganjajo iz ukaznega poziva, medtem ko VafAFT deluje kot samostojna aplikacija. Ko smo zaključili z anotacijo vseh vzorcev, smo v teh anotiranih vzorcih skušali poiskati vzročne mutacije, ki smo jih pridobili predhodno, pri čemer smo uporabili tudi orodje za filtriranje SnpSift. Rezultati: Rezultati anotacije z izbranimi orodji so se med posameznimi orodji nekoliko razlikovali pri vrednostih vmesnih parametrov, ki jih orodja izračunajo na podlagi svojih algoritmov, medtem ko smo pri zaznavanju tipov in lokacij različic ter tega, kaj določena različica povzroči, dobili dokaj podobne rezultate. Rezultati primerjave orodij, ki smo jo izvedli na podlagi tega, ali je orodje zaznalo vzročno mutacijo v vzorcu, pa so nam pokazali, da se orodja med seboj kar precej razlikujejo, saj je orodje ANNOVAR zaznalo 50 % vseh vzročnih mutacij, VarAFT 35,7 %, Exomiser 28,5 %, medtem ko sta orodji SnpEff in VEP zaznali le 21,4 % vseh vzročnih mutacij. Diskusija: Ugotovili smo, da je bilo orodje ANNOVAR najuspešnejše pri zaznavanju vzročnih mutacij. Zaradi majhnega števila vzorcev (14 vzročnih mutacij v 24 vzorcih) bo rezultate naše primerjave učinkovitosti preiskovanih orodij potrebno potrditi še na večjem številu vzorcev.
Keywords:	NGS, anotacija, bioinformatika, eksom
Place of publishing:	Maribor
Publisher:	[M. Toplak]
Year of publishing:	2021
PID:	20.500.12556/DKUM-80939
UDC:	575.112(043.2)
COBISS.SI-ID:	92294147
Publication date in DKUM:	10.01.2022
Views:	1508
Downloads:	123
Metadata:
Categories:	FZV
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Licences

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

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	23.11.2021

Secondary language

Language:	English
Title:	Comparison of bioinformatic tools for annotation of exome data obtained with dna next-generation sequencing
Abstract:	Introduction: Genomic annotation is a key step that comes in place, once we are done with the sequencing of DNA, because it helps us to identify importnant functional elements of the sequence as well as provides us with the meaning of the nuceotide sequence of interest. Exome is defined as a sequence which conatins all exones of the protein coding genes in genome and it represents between 1% and 2% of total genome, however it contains about 85% of variants that are known to cause medical conditions. Methods: In the empirical part, first we downloaded and installed all of the selected annotation tools to our desktop computer and then we performed annotation on all of our 24 samples, all of which were in VCF format and previously analyzed at Center for human genetics and pharmacogenomics Faculty of Medicine, University of Maribor. The tools we selected for the thesis were ANNOVAR, Exomiser, VarAFT, SnpEff and Ensembl VEP. All of those tools with an exception of VarAFT, which works as a stand alone application, are command line tools. Once we were done with the annotation process of all of our samples, we inspected our annotated samples for a previously obtained positive findings with a help of SnpSift filtering tool. Results: Obtained annotation results with selected tools have shown some different values of some annotated attributes, while the results of variant types and their locations as well as the consequences of a variant present, were similar. Tools were then compared based on whether they were able to detect a positive finding in a sample. The results of the comparisson showed that the tools differed between each other since ANNOVAR was able to detect 50% of all the positive findings, VarAFT detected 35,7%, Exmosier detected 28,5%, while SnpEff and VEP both detected only 21,4% of all findings. Conclusion: ANNOVAR tool was the most successful tool based on its ability to detect a positive finding in samples, at this point we also have to mention a fact that this results do not hold a strong statistical power since we only had 14 positive findings in all of the 24 samples.
Keywords:	NGS, annotation, bioinformatics, exome

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