biotmle 1.1.5:
- An option for applying this methodology to next-generation sequencing data has
  been added, based on the popular "voom" transform of the limma R package.
- Facilities for parallelized computation have been completely re-implemented:
  current routines favor a combination of future and BiocParallel.
- The method for estimating biomarkers based on an observed outcome has been
  removed (temporarily). Inference based on this method requires re-thinking.
- A full suite of unit tests have been added, covering most package functions.

biotmle 1.0.0:
- The first release of this package was made as part of Bioconductor 3.5, in
   2016.

The biotmle R package provides routines for the method first described in the
the technical manuscript [1] and the software paper [2]:

1. Nima S. Hejazi, Sara Kherad-Pajouh, Mark J. van der Laan, Alan E. Hubbard.
   Variance Stabilization of Targeted Estimators of Causal Parameters in
   High-Dimensional Settings. https://arxiv.org/abs/1710.05451

2. Nima S. Hejazi, Weixin Cai, Alan E. Hubbard. biotmle: Targeted Learning for
   Biomarker Discovery. The Journal of Open Source Software, 2(15), 2017.
   https://dx.doi.org/10.21105/joss.00295