We just published a correction to our 2016 eLife paper.
While we were preparing the code to share it on Github, we discovered an error in calling drug resistance mutations (DRMs) in the protease gene in 140 sequences in our dataset (out of 6,717 sequences). The mistake was related to how R reads in data using read.table(). Even though the error only affected 2% of the sequences, it affected all downstream analysis and multiple figures had to be updated to reflect this correction. The resulting changes are minor and do not substantially change the conclusions and in some cases make them stronger.
When the analysis is updated with new numbers for these 140 sequences, all of our conclusions hold qualitatively, although the points in some figures shift slightly quantitatively. In fact, updating to the correct DRM calling for these sequences results in estimates for two treatments that are more in line with the expectations laid out in our paper.
As an illustration of this effect, we show here a version of Figure 4, which appeared in the paper (although has been slightly altered here for readability), and the shift of the model coefficients after correcting the 140 sequences of DRM calling. As you can see, the shifts are minor in most cases, and only serve to strengthen our conclusions for two of the PI treatments (points in the middle of the figure in light blue).
Figure 4, from the paper (slightly altered here for readability) shows the shift of the model coefficients after correcting the 140 sequences of DRM calling. The shifts are minor in most cases, and only serve to strengthen our conclusions for two of the PI treatments (points in the middle of the figure in light blue).
After finding the original mistake, we spent a lot of time going through all of the code for the paper and found a few other small mistakes in the description of the analysis. In all cases, the mistakes were minor.
The eLife editors and staff were very helpful in the entire process.
Feder, Alison F., et al. “More effective drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1.” Elife 5 (2016): e10670. Link.