Hybridization probes for target sequences can be made based on melting temperature value calculated by R package 'TmCalculator' <https://CRAN.R-project.org/package=TmCalculator> and methods extended from Beliveau, B. J.,(2018) <doi:10.1073/pnas.1714530115>, and those hybridization probes can be used to capture specific target regions in fluorescence in situ hybridization and next generation sequence experiments.

Fast estimation of binomial spatial probit regression models with spatial autocorrelation for big datasets.

Computes predicted probabilities and marginal effects for 
  binary & ordinal logit and probit, (partial) generalized ordinal & 
  multinomial logit models estimated with the glm(), clm() (in the 
  'ordinal' package), and vglm() (in the 'VGAM' package) functions.

Estimates unsupervised outlier probabilities for multivariate numeric data with many observations from a nonparametric outlier statistic.

Performs elementary probability calculations on finite sample spaces, which may be represented by data frames  or lists.
    This package is meant to rescue some widely used functions from the archived 'prob' package (see <https://cran.r-project.org/src/contrib/Archive/prob/>).
    Functionality includes setting up sample spaces, counting tools, defining probability spaces, performing set algebra, calculating probability and conditional probability, tools for simulation and checking the law of  large numbers, adding random variables, and finding marginal distributions.  Characteristic functions for all base R distributions are included.

It allows the user to determine sample sizes, select probabilistic samples,
 make estimates of different parameters for the total finite population and in studio domains,
 using the main design drawings.

An interactive document on  the topic of basic probability using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at  <https://analyticmodels.shinyapps.io/BayesShiny/>.

Utilities for multiple hypothesis testing, companion datasets from "Probability and Statistics for Economics and Business: An Introduction Using R" by Jason Abrevaya (MIT Press, under contract).