Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Near-optimal Assembly for Shotgun Sequencing with Noisy Reads

Ka Kit Lam, David Tse and Asif Khalak

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2014-10
January 30, 2014

http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-10.pdf

Abstract. Recent work identified the fundamental limits on the information requirements in terms of read length and coverage depth required for successful de novo genome reconstruction from shotgun sequencing data, based on the idealistic assumption of no errors in the reads (noiseless reads). In this work, we show that even when there is noise in the reads, one can successfully reconstruct with information requirements close to the noiseless fundamental limit. A new assembler, X-phased Multibridging, is designed based on a probabilistic model of the genome. It is shown through analysis to perform well on the model, and through simulations to perform well on real genomes.

Advisor: David Tse


BibTeX citation:

@mastersthesis{Lam:EECS-2014-10,
    Author = {Lam, Ka Kit and Tse, David and Khalak, Asif},
    Title = {Near-optimal Assembly for Shotgun Sequencing with Noisy Reads},
    School = {EECS Department, University of California, Berkeley},
    Year = {2014},
    Month = {Jan},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-10.html},
    Number = {UCB/EECS-2014-10},
    Abstract = {Abstract. Recent work identified the fundamental limits on the information requirements in terms of read length and coverage depth required for successful de novo genome reconstruction from shotgun sequencing data, based on the idealistic assumption of no errors in the reads (noiseless reads). In this work, we show that even when there is noise in the reads, one can successfully reconstruct with information requirements close to the noiseless fundamental limit. A new assembler, X-phased Multibridging, is designed based on a probabilistic model of the genome. It is shown through analysis to perform well on the model, and through simulations to perform well on real genomes.}
}

EndNote citation:

%0 Thesis
%A Lam, Ka Kit
%A Tse, David
%A Khalak, Asif
%T Near-optimal Assembly for Shotgun Sequencing with Noisy Reads
%I EECS Department, University of California, Berkeley
%D 2014
%8 January 30
%@ UCB/EECS-2014-10
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-10.html
%F Lam:EECS-2014-10