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. 2016 Apr 28;32(11):1670–1677. doi: 10.1093/bioinformatics/btw217

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© The Author 2016. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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Fig. 6. — Analysis of different misassembly removal strategies. (top) The bar plot represents the performance of various removal strategy in terms of percentage of misassemblies removed on Brain dataset. Single-k cluster removal (white bar) and 300 bp length cutoff based removal (grey bar) removes a high percentage of misassemblies. A combination of both methods (black bar) performs better than applying only one strategy. (bottom) Comparison of 80%-hit improvement rate and misassembly rate for all computed assemblies (see ‘Methods’)