prikaz prve stranice dokumenta Memorijski učinkovita pohrana genotipova
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undergraduate thesis
Memorijski učinkovita pohrana genotipova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:871446
Šandrk, Marko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Šandrk, M. (2019). Memorijski učinkovita pohrana genotipova (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:871446

Šandrk, Marko. "Memorijski učinkovita pohrana genotipova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:871446

Šandrk, Marko. "Memorijski učinkovita pohrana genotipova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:871446

Šandrk, M. (2019). 'Memorijski učinkovita pohrana genotipova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 14 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:871446

Šandrk M. Memorijski učinkovita pohrana genotipova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2025 January 14] Available at: https://urn.nsk.hr/urn:nbn:hr:168:871446

M. Šandrk, "Memorijski učinkovita pohrana genotipova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:871446

Metadata
TitleMemorijski učinkovita pohrana genotipova
Title (english)Memory-efficient genotype storage
AuthorMarko Šandrk
MentorMirjana Domazet-Lošo (mentor)
Committee memberMirjana Domazet-Lošo (predsjednik povjerenstva)
Committee memberBoris Vrdoljak (član povjerenstva)
Committee memberBoris Milašinović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-09-17, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Razvojem novih i poboljšanih metoda sekvenciranja, te opadanjem cijene sekvenciranja, dolazi se do sve većih skupova genomskih podataka i to sve većom brzinom. Sukladno tome, javlja se problematika memorijski učinkovitog skladištenja takvih podataka. Razvijene su razne metode za sažeti prikaz genotipova, od posebnih formata zapisa do algoritama za sažimanje. Ipak, nijedna od dosadašnjih tehnika nije se pokazala dugoročno poželjnom. GenoType Compressor (GTC) novi je algoritam specijaliziran za sažimanje podataka o genotipovima zapisanim u „variant call formatu” (VCF). Prva istraživanja pokazuju njegovu premoć u stupnju kompresije, ali i u vremenu pristupa sažetim podacima nad sličnim algoritmima. U ovom radu implementirana je osnovna verzija algoritma GTC te su analizirane performanse algoritma s obzirom na različite ulazne skupove i parametre. Također, usporedio sam implementaciju ostvarenu u okviru ovog rada s originalnom implementacijom GTC-a.
Abstract (english)
With the development of new and improved sequencing methods and with the reducing costs of genotype sequencing, more and more data is being collected with increased rates. This leads us to a problem of managing memory-efficient storage of such data. Various different methods of compressed data representation have been developed ranging from special data formats to compression algorithms. However, neither of former methods proved to be sufficiently acceptable in the long term. GenoType Compressor (GTC) is a new algorithm highly specialised for compression of genotype data stored in „variant call format” (VCF). Preliminary research place GTC high above it's competition in terms of compression rate and lower data access times. In this paper, a basic version of GTC algorithm is implemented and its performance is analyzed on different input data sets. Moreover, the implementiation of GTC developed in this thesis is compared with the original implementation of GTC algorithm.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:871446
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
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Created on2020-01-07 22:16:17