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. 2018 Apr 18;34(19):3273–3280. doi: 10.1093/bioinformatics/bty307

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© The Author(s) 2018. 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. 3. — Comparison of assemblies generated from ORNA, Diginorm and TIS reduced datasets. Each point on a line corresponds to a different parametrization of the algorithms. The amount of data reduction (x-axis) is compared against the assembly performance measured as % of complete (y-axis, see text). (a) and (d) Represent TransABySS assemblies (k = 21) applied on normalized brain and hESC data, respectively. (b) and (e) Represent Trinity assemblies (k = 25) and (c) and (f) represent Oases multi-kmer assemblies applied on normalized brain and hESC data, respectively