Package for high-throughput data processing, outlier detection,
noise removal and dynamic modeling
Description
The biosvd package contains functions to reduce the input
data set from the feature x assay space to the reduced
diagonalized eigenfeature x eigenassay space, with the
eigenfeatures and eigenassays unique orthonormal superpositions
of the features and assays, respectively. Results of SVD
applied to the data can subsequently be inspected based on
generated graphs, such as a heatmap of the eigenfeature x assay
matrix and a bar plot with the eigenexpression fractions of all
eigenfeatures. These graphs aid in deciding which eigenfeatures
and eigenassays to filter out (i.e., eigenfeatures representing
steady state, noise, or experimental artifacts; or when applied
to the variance in the data, eigenfeatures representing
steady-scale variance). After possible removal of steady state
expression, steady-scale variance, noise and experimental
artifacts, and after re-applying SVD to the normalized data, a
summary html report of the eigensystem is generated, containing
among others polar plots of the assays and features, a table
with the list of features sortable according to their
coordinates, radius and phase in the polar plot, and a
visualization of the data sorted according to the two selected
eigenfeatures and eigenassays with colored feature/assay
annotation information when provided. This gives a global
picture of the dynamics of expression/intensity levels, in
which individual features and assays are classified in groups
of similar regulation and function or similar cellular state
and biological phenotype.