Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 28 June 2020 doi:10.20944/preprints202006.0324.v1 Methods for De-novo Genome Assembly Arash Bayat∗1,3, Hasindu Gamaarachchi1, Nandan P Deshpande2, Marc R Wilkins2, and Sri Parameswaran1 1School of Computer Science and Engineering, UNSW, Australia 2Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, UNSW, Australia 3Health and Biosecurity, CSIRO, Australia June 25, 2020 Abstract Despite advances in algorithms and computational platforms, de-novo genome assembly remains a chal- lenging process. Due to the constant innovation in sequencing technologies (Sanger, SOLiD, Illumina, 454 , PacBio and Oxford Nanopore), genome assembly has evolved to respond to the changes in input data type. This paper includes a broad and comparative review of the most recent short-read, long-read and hybrid assembly techniques. In this review, we provide (1) an algorithmic description of the important processes in the workflow that introduces fundamental concepts and improvements; (2) a review of existing software that explains possible options for genome assembly; and (3) a comparison of the accuracy and the performance of existing methods executed on the same computer using the same processing capabilities and using the same set of real and synthetic datasets. Such evaluation allows a fair and precise comparison of accuracy in all aspects. As a result, this paper identifies both the strengths and weaknesses of each method. This com- parative review is unique in providing a detailed comparison of a broad spectrum of cutting-edge algorithms and methods. Availability: https://arashbayat.github.io/asm ∗To whom correspondence should be addressed. Email:
[email protected] 1 © 2020 by the author(s).