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Correction

Correction: Machine learning approach yields epigenetic biomarkers of food allergy: A novel 13-gene signature to diagnose clinical reactivity

  • The PLOS ONE Staff

In the Introduction, there is an error in the third sentence of the third paragraph. The correct sentence is: As a result, food challenges are often under performed, leading to an overdiagnosis of FA [9].

There is an error in Table 6. The vales in column 4 "Average Accuracy" are incorrect. The publisher apologizes for the error. Please see the correct Table 6 here.

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Table 6. Average hidden data accuracy across a large number of dataset permutations.

https://doi.org/10.1371/journal.pone.0220470.t001

Reference

  1. 1. Alag A (2019) Machine learning approach yields epigenetic biomarkers of food allergy: A novel 13-gene signature to diagnose clinical reactivity. PLoS ONE 14(6): e0218253. https://doi.org/10.1371/journal.pone.0218253 pmid:31216310

Citation: The PLOS ONE Staff (2019) Correction: Machine learning approach yields epigenetic biomarkers of food allergy: A novel 13-gene signature to diagnose clinical reactivity. PLoS ONE 14(7): e0220470. https://doi.org/10.1371/journal.pone.0220470

Published: July 24, 2019

Copyright: © 2019 The PLOS ONE Staff. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.