HDMD: Statistical Analysis Tools for High Dimension Molecular Data (HDMD)
Version 1.2

High Dimensional Molecular Data (HDMD) typically have many more variables or dimensions than observations or replicates (D>>N). This can cause many statistical procedures to fail, become intractable, or produce misleading results. This package provides several tools to reduce dimensionality and analyze biological data for meaningful interpretation of results. Factor Analysis (FA), Principal Components Analysis (PCA) and Discriminant Analysis (DA) are frequently used multivariate techniques. However, PCA methods prcomp and princomp do not reflect the proportion of total variation of each principal component. Loadings.variation displays the relative and cumulative contribution of variation for each component by accounting for all variability in data. When D>>N, the maximum likelihood method cannot be applied in FA and the the principal axes method must be used instead, as in factor.pa of the psych package. The factor.pa.ginv function in this package further allows for a singular covariance matrix by applying a general inverse method to estimate factor scores. Moreover, factor.pa.ginv removes and warns of any variables that are constant, which would otherwise create an invalid covariance matrix. Promax.only further allows users to define rotation parameters during factor estimation. Similar to the Euclidean distance, the Mahalanobis distance estimates the relationship among groups. pairwise.mahalanobis computes all such pairwise Mahalanobis distances among groups and is useful for quantifying the separation of groups in DA. Genetic sequences are composed of discrete alphabetic characters, which makes estimates of variability difficult. MolecularEntropy and MolecularMI calculate the entropy and mutual information to estimate variability and covariability, respectively, of DNA or Amino Acid sequences. Functional grouping of amino acids (Atchley et al 1999) is also available for entropy and mutual information estimation. Mutual information values can be normalized by NMI to account for the background distribution arising from the stochastic pairing of independent, random sites. Alternatively, discrete alphabetic sequences can be transformed into biologically informative metrics to be used in various multivariate procedures. FactorTransform converts amino acid sequences using the amino acid indices determined by Atchley et al 2005.

AuthorLisa McFerrin
Date of publication2013-02-27 07:31:03
MaintainerLisa McFerrin <lgmcferr@ncsu.edu>
LicenseGPL (>= 2)
Version1.2
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("HDMD")

Getting started

Package overview

Popular man pages

AA54: Normalized Amino Acid Indices quantifying 54 various...
bHLH288: Alignment of basic Helix Loop Helix (bHLH) domain data
HDMD-package: Structural Analysis Tools for High Dimensional Molecular Data
Loadings.variation: Proportional and Cumulative Variation of Loading Components
NMI: Normalized Mutual Information
pairwise.mahalanobis: Mahalanobis distances for grouped data
Promax.only: Promax rotation (without prior Varimax rotation)
See all...

All man pages Function index File listing

Man pages

AA54: Normalized Amino Acid Indices quantifying 54 various...
AAMetric: Amino Acid Metric Solution using R (Atchley et al 2005)
AAMetric.Atchley: Amino Acid Metric Solution (Atchley et al 2005)
AminoAcids: Amino Acid Properties
bHLH288: Alignment of basic Helix Loop Helix (bHLH) domain data
factor.pa.ginv: Principal Axis Factor Analysis when D>>N
FactorTransform: Metric Solution for Amino Acid characters
HDMD-package: Structural Analysis Tools for High Dimensional Molecular Data
Loadings.variation: Proportional and Cumulative Variation of Loading Components
MolecularEntropy: Molecular Entropy for DNA or Amino Acid Sequences
MolecularMI: Molecular Mutual Information
NMI: Normalized Mutual Information
pairwise.mahalanobis: Mahalanobis distances for grouped data
Promax.only: Promax rotation (without prior Varimax rotation)

Functions

AA54 Man page
AAGroups Man page
AAMetric Man page
AAMetric.Atchley Man page
AAbyGroup Man page
AminoAcids Man page
FactorTransform Man page Source code
FactorTransform.default Man page Source code
FactorTransform.vector Man page Source code
HDMD Man page
HDMD-package Man page
Loadings.variation Man page Source code
MolecularEntropy Man page Source code
MolecularMI Man page Source code
NMI Man page Source code
Promax.only Man page Source code
bHLH288 Man page
factor.pa.ginv Man page Source code
hydrophobic Man page
pairwise.mahalanobis Man page Source code
polar Man page
small Man page

Files

MD5
R
R/HDMD_package.R
R/bHLH288.R
R/AA54.R
NAMESPACE
man
man/Promax.only.Rd
man/pairwise.mahalanobis.Rd
man/NMI.Rd
man/MolecularMI.Rd
man/MolecularEntropy.Rd
man/Loadings.variation.Rd
man/HDMD-package.Rd
man/FactorTransform.Rd
man/factor.pa.ginv.Rd
man/bHLH288.Rd
man/AminoAcids.Rd
man/AAMetric.Rd
man/AAMetric.Atchley.Rd
man/AA54.Rd
DESCRIPTION
HDMD documentation built on May 19, 2017, 8:57 a.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.