Software
Toolboxes
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4n Toolbox
This toolbox contains the 4N algorithm and supplementary functions explained in the publication
"Inferring protein-protein interaction complexes from immunoprecipitation data (to be published)"
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Peak Generation
Contents
emgpeak: Generate exponential modified Gaussian peaks
fspeak: Generate a number of Fraser-Suzuki peaks
gspeak: Generate a number of Gaussian peaks
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Noise Generation
Contents
clnoise: Generate coloured noise records, given autocorrelation function of desired noise
firnoise: Generate noise records using a known noise shaping filter
fonoise: Generate first order bandlimited white noise
fnoise: Generate noise according to the arctangent model. This is an approximation of 1/f noise (flickernoise)
mnoise: Generate a set signals, that have correlation in time and mutual correlation
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Plotting Routines
Contents
addDate: add a date stamp to a plot
defplot: Set default plotting options
ellipse: Draw ellipse
nplot: Normalized plot of set of curves
nsplot: Normalized stacked plot of set of curves
paxis: Normalized stacked plot of set of curves
plotmixtdes: plot a mixture design
plotscrs: plot (PCA) scores
saveppt: Save MATLAB figure window to an powerpoint file
splot: Stack several curves in one plot above each other
suptitle: Title in a figure with subplots
tilefigs: Tile all created figures on the screen
xerrbar: Plot errorbars in the x-direction
- Additional Statistical Routines
Contents
adtest: Anderson-Darling normality test to test whether data is normally distributed
grubbs: Grubbs outlier test
trandt: Randomisation t-test for comparing the predictive accuracy of two (multivariate) models (A and B) for the same TEST dataset
whtest: Test whether a vector is white noise sequence
- Spectral tools
Contents
readspec: Reads a list of spectral data files created by various spectrometers and spectrometric software
HPJCAMP2uns: Convert HPJCAMP ASCII files to ASCII files that can be used by Unscrambler
absspec: Calculate absorbance spetrum from a number of single beam spectra of sample and one single beam spectrum of the background
readsbs: Read a file containing single beam spectra (BOMEM MB-155)
readspc: Read SpectraCalc file (BOMEM MB-155, KAISER RAMAN spectrometer)
readJCAMP: Read a JCAMP-DX file
readHPJCAMP: Read HP-UVvis data created by macro "readall" on the HP spectrometer
readPEasc: Read one spectrum (Perkin Elmer)
readPEcvs: Read spectra (Perkin Elmer Timebase)
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Vertex-edge incidence matrix by using the zero slopes method.
Fourth order approximation of the time derivatives of metabolite concentrations and calculation of the Jacobian.
Time lagged correlation matrix
Reference:
Reverse engineering of metabolic networks, a critical assessment
Diana M. Hendrickx, Margriet M. W. B. Hendriks, Paul H. C. Eilers, Age K. Smilde and Huub C. J. Hoefsloot
Mol. BioSyst, Advance Article (2011)
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Grey component analysis
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Endocrine pulse identification
Reference:
Endocrine pulse identification using penalized methods and a minimum set of
assumptions
Daniel J. Vis, Johan A. Westerhuis, Huub C. J. Hoefsloot, Hanno Pijl, Ferdinand Roelfsema,
Jan van der Greef, and Age K. Smilde
Am J Physiol Endocrinol Metab Vol. 298 (2009), pages 146-155, 2010
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Crossfit: Model generating Global, Local and Crossfit models of crossed data with two factors, time and treatment.
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MLPLSDA: Multilevel Data Analysis
Tutorial Multilevel Data Analysis
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RV_modified: Modified RV-coefficient for matrix correlations for high dimensional data
Reference: Matrix correlations for high-dimensional data: the modified RV-coefficient
A.K. Smilde, H.A.L. Kiers, S. Bijlsma, C.M. Rubingh and M.J. van Erk
Bioinformatics Advance Access published December 10 2008 (Oxford University Press)
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DQ2: Calculates the discriminant Q2 value
Reference: Discriminant Q2 (DQ2) for improved discrimination in PLSDA models
Johan A. Westerhuis, Ewoud J. J. van Velzen, Huub C. J. Hoefsloot and Age K. Smilde
Metabolomics: Springer link date 30 August 2008
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PCDA: Principal Component Discriminant Analysis
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MALS: Maximum Likelihood Scaling (MALS)
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ASCA: ANOVA Simultaneous Component Analysis
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CPDScv: Crossvalidation for CPDS
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DOSC: Direct Orthogonal Signal Correction
- MMC_CRM: Multiway Multiblock Component and Covariates Regression Models
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Bagged Clustering k-means: Bagged Clustering k-means
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MSCA: Multilevel Simultaneous Component Analysis
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PCAW: Weighted Principal Component Analysis
- PCOVR: Principal Covariates Regression/PARAFAC
- SmoothPCA: Smooth PCA