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Correction to: A statistical framework for analyzing deep mutational scanning data
Genome Biology volume 19, Article number: 17 (2018)
- The original article was published in Genome Biology 2017 18:150
After publication of our article  it was brought to our attention that a line of code was missing from our program to combine the within-replicate variance and between-replicate variance. This led to an overestimation of the standard errors calculated using the Enrich2 random-effects model.
This programming error has been corrected in v1.2.0 of the software, available from .
We have reanalyzed the data in the paper using v1.2.0. The results are very similar and do not significantly affect any of the manuscript’s conclusions. Notably, none of the numeric values quoted in the main text change.
We would like to thank Jörn Schmiedel for alerting us to this issue, helping us reproduce it and testing the fix.
Rubin AF, Gelman H, Lucas N, Bajjalieh SM, Papenfuss AT, Speed TP, et al. A statistical framework for analyzing deep mutational scanning data. Genome Biol. 2017;18(1):150.
Jiang L, Liu P, Bank C, Renzette N, Prachanronarong K, Yilmaz LS, et al. A balance between inhibitor binding and substrate processing confers influenza drug resistance. J Mol Biol. 2016;428:538–53.
The original article can be found online at https://doi.org/10.1186/s13059-017-1272-5.
Supplementary figures. (PDF 423 kb)
Replicate correlation tables. (XLSX 14 kb)
Individually validated variants of the neuraminidase gene. (XLSX 12 kb)
Variants with higher scores than wild-type in the presence of oseltamivir. (XLSX 15 kb)
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Rubin, A.F., Gelman, H., Lucas, N. et al. Correction to: A statistical framework for analyzing deep mutational scanning data. Genome Biol 19, 17 (2018). https://doi.org/10.1186/s13059-018-1391-7