Differential Expression Analysis Using a Bottom-Up Model (denoiSeq)
Given count data from two conditions, it determines which transcripts are differentially expressed across the two conditions using Bayesian inference of the parameters of a bottom-up model for PCR amplification. This model is developed in Ndifon Wilfred, Hilah Gal, Eric Shifrut, Rina Aharoni, Nissan Yissachar, Nir Waysbort, Shlomit Reich Zeliger, Ruth Arnon, and Nir Friedman (2012), <http://…/15865.full>, and results in a distribution for the counts that is a superposition of the binomial and negative binomial distribution.

Apply Functions to Multiple Multidimensional Arguments (multiApply)
The base apply function and its variants, as well as the related functions in the ‘plyr’ package, typically apply user-defined functions to a single argument (or a list of vectorized arguments in the case of mapply). The ‘multiApply’ package extends this paradigm to functions taking a list of multiple unidimensional or multidimensional arguments (or combinations thereof) as input, which can have different numbers of dimensions as well as different dimension lengths.

Basic Functions for Pre-Processing Microarrays (PreProcess)
Provides classes to pre-process microarray gene expression data as part of the OOMPA collection of packages described at <http://…/>.

Visualize Reproducibility and Replicability in a Comparison of Scientific Studies (scifigure)
Users may specify what fundamental qualities of a new study have or have not changed in an attempt to reproduce or replicate an original study. A comparison of the differences is visualized. Visualization approach follows Patil, Peng, and Leek (2016) <doi:10.1101/066803>.

Two Stage Forecasting (TSF) for Long Memory Time Series in Presence of Structural Break (TSF)
Forecasting of long memory time series in presence of structural break by using TSF algorithm by Papailias and Dias (2015) <doi:10.1016/j.ijforecast.2015.01.006>.