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. 2014 Jul 26;15(7):410. doi: 10.1186/s13059-014-0410-6

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© Davidson and Oshlack; licensee BioMed Central Ltd 2014

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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A comparison of the performance of different clustering approaches. For the assembler’s own clustering (Trinity or Oases), CD-HIT-EST and Corset we show the precision against the recall. The precision is the ratio of true positives over true positives plus false positives and the recall is the ratio of true positives over true positives plus false negatives. We show the results for six different assemblies: (A) chicken data assembled with Trinity; (B) chicken data assembled with Oases; (C) human data assembled with Trinity; (D) human data assembled with Oases; (E) yeast data assembled with Trinity; and (F) yeast data assembled with Oases. The X indicates perfect clustering.