NMF v0.23.0


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Algorithms and Framework for Nonnegative Matrix Factorization (NMF)

Provides a framework to perform Non-negative Matrix Factorization (NMF). The package implements a set of already published algorithms and seeding methods, and provides a framework to test, develop and plug new/custom algorithms. Most of the built-in algorithms have been optimized in C++, and the main interface function provides an easy way of performing parallel computations on multicore machines.



Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have demonstrated its ability to extract meaningful information from high-dimensional data such as gene expression microarrays. Developments in NMF theory and applications have resulted in a variety of algorithms and methods. However, most NMF implementations have been on commercial platforms, while those that are freely available typically require programming skills. This limits their use by the wider research community.


Our objective is to provide the bioinformatics community with an open-source, easy-to-use and unified interface to standard NMF algorithms, as well as with a simple framework to help implement and test new NMF methods. For that purpose, we have developed a package for the R/BioConductor platform. The package ports public code to R, and is structured to enable users to easily modify and/or add algorithms. It includes a number of published NMF algorithms and initialization methods and facilitates the combination of these to produce new NMF strategies. Commonly used benchmark data and visualization methods are provided to help in the comparison and interpretation of the results.


The NMF package helps realize the potential of Nonnegative Matrix Factorization, especially in bioinformatics, providing easy access to methods that have already yielded new insights in many applications.

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Functions in NMF

Name Description
NMFSeed-class Base class that defines the interface for NMF seeding methods.
nmf_update.lee_R NMF Algorithm/Updates for Frobenius Norm
nmf_update.brunet_R NMF Algorithm/Updates for Kullback-Leibler Divergence
NMF-class Generic Interface for Nonnegative Matrix Factorisation Models
NMFList-class Class for Storing Heterogeneous NMF fits
NMF-deprecated Deprecated Functions in the Package NMF
NMF-package Algorithms and framework for Nonnegative Matrix Factorization (NMF).
NMF-defunct Defunct Functions and Classes in the NMF Package
NMFOffset-class NMF Model - Nonnegative Matrix Factorization with Offset
NMFStrategy-class Virtual Interface for NMF Algorithms
NMFfitX-class Virtual Class to Handle Results from Multiple Runs of NMF Algorithms
NMFfit-class Base Class for to store Nonnegative Matrix Factorisation results
NMFStrategyIterative-class Interface for Algorithms: Implementation for Iterative NMF Algorithms
NMFfitX Factory Method for Multiple NMF Run Objects
NMFStrategyFunction-class Interface for Single Function NMF Strategies
basis Accessing NMF Factors
NMFStrategy Factory Method for NMFStrategy Objects
.atrack Annotation Tracks
canFit Testing Compatibility of Algorithm and Models
c,NMF-method Concatenating NMF Models
NMFns-class NMF Model - Nonsmooth Nonnegative Matrix Factorization
advanced-NMF Advanced Usage of the Package NMF
NMFstd-class NMF Model - Standard model
aheatmap Annotated Heatmaps
connectivity Clustering Connectivity and Consensus Matrices
consensus,NMFfitX1-method Returns the consensus matrix computed while performing all NMF runs, amongst which object was selected as the best fit.
Strategy-class Generic Strategy Class
basiscor Correlations in NMF Models
fit Extracting Fitted Models
NMFfitX1-class Structure for Storing the Best Fit Amongst Multiple NMF Runs
fcnnls Fast Combinatorial Nonnegative Least-Square
getRNG1 Extracting RNG Data from NMF Objects
algorithmic-NMF Generic Interface for Algorithms
NMFfitXn-class Structure for Storing All Fits from Multiple NMF Runs
.fcnnls Internal Routine for Fast Combinatorial Nonnegative Least-Squares
summary Assessing and Comparing NMF Models
bioc-NMF Specific NMF Layer for Bioconductor
ccBreaks Generate Break Intervals from Numeric Variables
esGolub Golub ExpressionSet
nmfAlgorithm.SNMF_R NMF Algorithm - Sparse NMF via Alternating NNLS
cluster_mat Cluster Matrix Rows in Annotated Heatmaps
checkErrors Error Checks in NMF Runs
cophcor Cophenetic Correlation Coefficient
consensus,NMFfitXn-method Computes the consensus matrix of the set of fits stored in object, as the mean connectivity matrix across runs.
ccPalette Builds a Color Palette from Compact Color Specification
nmfAlgorithm Listing and Retrieving NMF Algorithms
gfile Open a File Graphic Device
tryViewport Internal Grid Extension
basisnames Dimension names for NMF objects
deviance Distances and Objective Functions
algorithm,NMFList-method Returns the method names used to compute the NMF fits in the list. It returns NULL if the list is empty.
ccRamp Builds a Color Ramp from Compact Color Specification
nmfApply Apply Function for NMF Objects
ccSpec Extract Colour Palette Specification
fitted Fitted Matrix in NMF Models
consensushc Hierarchical Clustering of a Consensus Matrix
nmfFormals Showing Arguments of NMF Algorithms
registerDoBackend Utilities and Extensions for Foreach Loops
nmf_update.euclidean_offset.h NMF Multiplicative Update for NMF with Offset Models
offset,NMFfit-method Returns the offset from the fitted model.
nmfModel Factory Methods NMF Models
nmfCheck Checking NMF Algorithm
nmfEstimateRank Estimate Rank for NMF Models
nbasis Dimension of NMF Objects
plot,NMFfit,missing-method Plots the residual track computed at regular interval during the fit of the NMF model x.
dispersion Dispersion of a Matrix
nmf Running NMF algorithms
parse_formula Simple Parsing of Formula
cutdendro Fade Out the Upper Branches from a Dendrogram
nmfSeed Seeding Strategies for NMF Algorithms
nmfReport Run NMF Methods and Generate a Report
compare-NMF Comparing Results from Different NMF Runs
nmfObject Updating NMF Objects
match_atrack Extending Annotation Vectors
heatmap-NMF Heatmaps of NMF Factors
randomize Randomizing Data
nmfWrapper Wrapping NMF Algorithms
purity Purity and Entropy of a Clustering
show,NMFOffset-method Show method for objects of class NMFOffset
pmax.inplace Updating Objects In Place
methods-NMF Registry for NMF Algorithms
residuals Residuals in NMF Models
show,NMFSeed-method Show method for objects of class NMFSeed
seed Interface for NMF Seeding Methods
nmf.equal Testing Equality of NMF Models
nmf_update.KL.h NMF Multiplicative Updates for Kullback-Leibler Divergence
nmf_update.lsnmf Multiplicative Updates for LS-NMF
nmf_update.euclidean.h NMF Multiplicative Updates for Euclidean Distance
setNMFMethod Registering NMF Algorithms
nneg Transforming from Mixed-sign to Nonnegative Data
lverbose Internal verbosity option
nmf_update.ns NMF Multiplicative Update for Nonsmooth Nonnegative Matrix Factorization (nsNMF).
show,NMFfitXn-method Show method for objects of class NMFfitXn
parallel-NMF Utilities for Parallel Computations
options-NMF NMF Package Specific Options
staticVar Get/Set a Static Variable in NMF Algorithms
utils-NMF Utility Function in the NMF Package
sparseness Sparseness
objective,NMFfit-method Returns the objective function associated with the algorithm that computed the fitted NMF model object, or the objective value with respect to a given target matrix y if it is supplied.
show,NMFns-method Show method for objects of class NMFns
runtime,NMFList-method Returns the CPU time required to compute all NMF fits in the list. It returns NULL if the list is empty. If no timing data are available, the sequential time is returned.
scale.NMF Rescaling NMF Models
NMFStop Stopping Criteria for NMF Iterative Strategies
offset,NMFOffset-method Offsets in NMF Models with Offset
runtime.all,NMFfitXn-method Returns the CPU time used to perform all the NMF fits stored in object.
featureScore Feature Selection in NMF Models
predict Clustering and Prediction
[,NMF-method Sub-setting NMF Objects
revPalette Flags a Color Palette Specification for Reversion
profplot Plotting Expression Profiles
show,NMFStrategyIterative-method Show method for objects of class NMFStrategyIterative
show,NMFfit-method Show method for objects of class NMFfit
txtProgressBar Simple Progress Bar
rss Residual Sum of Squares and Explained Variance
rnmf Generating Random NMF Models
show,NMF-method Show method for objects of class NMF
is.nmf Testing NMF Objects
show,NMFList-method Show method for objects of class NMFList
show,NMFfitX-method Show method for objects of class NMFfitX
syntheticNMF Simulating Datasets
show,NMFfitX1-method Show method for objects of class NMFfitX1
rmatrix Generating Random Matrices
t.NMF Transformation NMF Model Objects
NMFSeed NMFSeed is a constructor method that instantiate NMFSeed objects.
setupBackend Computational Setup Functions
silhouette.NMF Silhouette of NMF Clustering
smoothing Smoothing Matrix in Nonsmooth NMF Models
bterms<- Fixed Terms in NMF Models
ibterms Fixed Terms in NMF Models
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Vignettes of NMF

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Last month downloads


Type Package
Date 2020-07-30
License GPL (>= 2)
URL http://renozao.github.io/NMF
LazyLoad yes
VignetteBuilder knitr
Collate 'colorcode.R' 'options.R' 'grid.R' 'atracks.R' 'aheatmap.R' 'algorithmic.R' 'nmf-package.R' 'rmatrix.R' 'utils.R' 'versions.R' 'NMF-class.R' 'transforms.R' 'Bioc-layer.R' 'NMFstd-class.R' 'NMFOffset-class.R' 'heatmaps.R' 'NMFns-class.R' 'nmfModel.R' 'fixed-terms.R' 'NMFfit-class.R' 'NMFSet-class.R' 'NMFStrategy-class.R' 'registry.R' 'NMFSeed-class.R' 'NMFStrategyFunction-class.R' 'NMFStrategyIterative-class.R' 'NMFplots.R' 'registry-algorithms.R' 'algorithms-base.R' 'algorithms-lnmf.R' 'algorithms-lsnmf.R' 'algorithms-pe-nmf.R' 'algorithms-siNMF.R' 'algorithms-snmf.R' 'data.R' 'extractFeatures.R' 'parallel.R' 'registry-seed.R' 'nmf.R' 'rnmf.R' 'run.R' 'seed-base.R' 'seed-ica.R' 'seed-nndsvd.R' 'setNMFClass.R' 'simulation.R' 'tests.R'
Packaged 2020-07-31 10:09:52 UTC; nsauwen
NeedsCompilation yes
Repository CRAN
Date/Publication 2020-08-01 05:10:06 UTC

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