Implements persistent row and column annotations for R matrices. The annotations associated with rows and columns are preserved after subsetting, transposition, and various other matrix-specific operations. Intended use case is for storing and manipulating genomic datasets which typically consist of a matrix of measurements (like gene expression values) as well as annotations about rows (i.e. genomic locations) and annotations about columns (i.e. meta-data about collected samples). But 'annmatrix' objects are also expected to be useful in various other contexts.

We curated 147 of expression array, from 3 species(human,mouse,rat), 
              3 companies('Affymetrix','Illumina','Agilent'), 
              by aligning the 'Fasta' sequences of all probes of each platform to their corresponding reference genome, 
              and then annotate them to genes.

Provides non-invasive annotation of package load calls 
    such as \code{library()}, \code{p_load()}, and \code{require()} so that we can have an idea of what 
    the packages we are loading are meant for.

Extraction of subsequences into FASTA files from GenBank annotations where gene names may vary among accessions. Borstein & O'Meara (2018) <doi:10.7717/peerj.5179>.

Provides functions to create image annotations through polygon outlining. Annotator has the same function as 'graphics::locator()' but achieves its purpose through drawing, rather than multiple mouse clicks. It is based on the 'htmlwidgets' package and 'fabric.js' JavaScript library <https://fabricjs.com/>.

Annuity Random Interest Rates proposes different techniques for the approximation of the present and final value of a unitary annuity-due or annuity-immediate considering interest rate as a random variable. Cruz Rambaud et al. (2017) <doi:10.1007/978-3-319-54819-7_16>. Cruz Rambaud et al. (2015) <doi:10.23755/rm.v28i1.25>.

Provides ANOCVA (ANalysis Of Cluster VAriability), a non-parametric statistical test
    to compare clustering structures with applications in functional magnetic resonance imaging
    data (fMRI). The ANOCVA allows us to compare the clustering structure of multiple groups
    simultaneously and also to identify features that contribute to the differential clustering.