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LRSim: a Linked Reads Simulator generating insights for better genome partitioning

View ORCID ProfileRuibang Luo, View ORCID ProfileFritz J. Sedlazeck, Charlotte A. Darby, Stephen M. Kelly, View ORCID ProfileMichael C. Schatz
doi: https://doi.org/10.1101/103549
Ruibang Luo
1Department of Computer Science, Johns Hopkins University
2Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine
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Fritz J. Sedlazeck
1Department of Computer Science, Johns Hopkins University
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Charlotte A. Darby
1Department of Computer Science, Johns Hopkins University
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Stephen M. Kelly
3Center for Health Informatics and Bioinformatics, New York University School of Medicine
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Michael C. Schatz
1Department of Computer Science, Johns Hopkins University
2Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine
4Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory
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Abstract

Motivation Linked reads are a form of DNA sequencing commercialized by 10X Genomics that uses highly multiplexed barcoding within microdroplets to tag short reads to progenitor molecules. The linked reads, spanning tens to hundreds of kilobases, offer an alternative to long-read sequencing for de novo assembly, haplotype phasing and other applications. However, there is no available simulator, making it difficult to measure their capability or develop new informatics tools.

Results Our analysis of 13 real linked read datasets revealed their characteristics of barcodes, molecules and partitions. Based on this, we introduce LRSim that simulates linked reads by emulating the library preparation and sequencing process with fine control of 1) the number of simulated variants; 2) the linked-read characteristics; and 3) the Illumina reads profile. We conclude from the phasing and genome assembly of multiple datasets, recommendations on coverage, fragment length, and partitioning when sequencing human and non-human genome.

Availability LRSIM is under MIT license and is freely available at https://github.com/aquaskyline/LRSIM

Contact rluo5{at}jhu.edu

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted January 26, 2017.
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LRSim: a Linked Reads Simulator generating insights for better genome partitioning
Ruibang Luo, Fritz J. Sedlazeck, Charlotte A. Darby, Stephen M. Kelly, Michael C. Schatz
bioRxiv 103549; doi: https://doi.org/10.1101/103549
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LRSim: a Linked Reads Simulator generating insights for better genome partitioning
Ruibang Luo, Fritz J. Sedlazeck, Charlotte A. Darby, Stephen M. Kelly, Michael C. Schatz
bioRxiv 103549; doi: https://doi.org/10.1101/103549

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