Naslov
Hidden Markov Model for Base Calling of MinION Nanopore Reads

Autori
Selak, Ana Marija

Vrsta, podvrsta i kategorija rada
Ocjenski radovi, diplomski rad, diplomski

Fakultet
Fakultet elektrotehnike i računarstva

Mjesto
Zagreb

Datum
02.03

Godina
2018

Stranica
20

Mentor
Šikić, Mile

Ključne riječi
MinION ; sequencer ; basecaller ; signal ; event ; Hidden Markov Model ; Baum-Welch ; Expectation Maximization ; Viterbi decoding

Sažetak
MinION, by Oxford Nanopore Technologies, is a third generation sequencer. Due to its small size and low cost it has become very popular. One of its disadvantages in comparison to more expensive and bigger sequencers is a higher error rate in basecalling. In order to reduce the error new basecallers are being developed. Signals received from the MinION are segmented into a list of events and are then translated into a nucleotide sequence by a basecaller. One of the basecallers is Nanocall, first open source basecaller. Based on the implementation of Nanocall, basecaller described in this work has been made. Implemented basecaller relies on Hidden Markov Model to represent the events as the observations and the nucleotides as the hidden states. It uses Baum- Welch algorithm to update the transition probabilities and Expectation Maximization to update the emission probabilities. Having a trained model, Viterbi algorithm is used to decode the sequence of events. Improvements of the basecaller are still being added in order to lower the error rate.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Računarstvo

POVEZANOST RADA