Software uses the dose-response models from the EPA BMDS software and ToxicR (developed by Matt Wheeler (matt.wheeler@nih.gov) to analyze high dimensional dose-response data, in particular gene expression data. The outputs of the software are gene and gene set level benchmark dose values.
Jason Phillips (jason.phillips@sciome.com) was the software engineer on BMDExpress 3 and Dan Svoboda (daniel.svoboda@sciome.com) was the primary design engineer. Scott Auerbach (auerbachs@niehs.nih.gov) led the project team.
The software is derivation of efforts by Longlong Yang (longlong.yang@nih.gov) that was originally released in 2007. (https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-8-387). It was updated in 2018 through a collaboration involving NTP, Sciome, Health Canada and the US EPA (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6513160/).
BMDExpress 1.0 is available here.
BMDExpress 2.0 is available here.
Details on the US EPA BMDS software can be found here.
Curve fit-based prefilter to identify dose responsive features more effectively
New maximum likelihood estimate models implimented (i.e., those used in the best model approach). These are the validated models that currently employed EPA's BMDS software.
Alternative confidence interval estimate method (Wald) that allows for more rapid curve fitting
Laplace and MCMC Bayesian model averaging based the approach used in the ToxicR package. The methods in ToxicR have undergone peer review and are published. The statistical details of the ToxicR model averaging approach has also been [published] (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9799099/) in the peer review literature
Forward toxicokinetic modeling to estimate internal dose levels based upon external dose BMD value
If you still have further questions, concerns, comments or suggestions, please contact Scott Auerbach (auerbachs@niehs.nih.gov) or Jason Phillips (jason.phillips@sciome.com).
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