Return names of samples where certain corrections are missing.
Opens an R markdown template for an easy and userfriendly analysis of EEM data.
Check size of EEMs
Importer function for generic csv files to be used with eem_read().
EEM sample data is extended to include all wavelengths in all samples
Exclude complete wavelengths or samples form data set
Export all samples of an eem_list
Correct names of EEM samples to match undiluted absorbance data.
Check your EEM, absorption and metadata before processing
Wrapper function to allow eem_inner_filter_effect (eemR) handling different cuvette lengths.
Multiply all EEMs with a matrix
Load original data from the drEEM tutorial and return it as eemlist
Load all eemlist obects saved in different Rdata or RDa files in a folder.
Create table that contains sample names and locations of files.
Check for NAs in EEM data
Missing values are interpolated within EEM data
Replace matched patterns in sample names
Modifying fluorescence data according to dilution.
15 fluorescence samples from drEEM used for examples.
2 fluorescence samples from drEEM that were excluded as outliers from the PARAFAC model.
Remove wavelengths, that are missing in at least one sample form the whole set.
Cut EEM data matching a given wavelength range
Import EEMs from generic csv tables (deprecated)
Set names of PARAFAC components
Extract names from PARAFAC model components
Calculate the core consistancy of an EEM PARAFAC model
Extract modelling information from a PARAFAC model.
Calculate raman area of EEM samples
Multiply EEMs with spectral correction vectors (Emission and Excitation)
Wrapper function to eem_raman_normalisation (eemR).
Smooth fluorescence data by calculating rolling mean along excitation wavelengths.
Plot fluorescence data from several samples split into several plots.
Determines the the biggest range of EEM spectrum where data is available from each sample.
Determine the range of fluorescence values in a set of samples
set parts of specific samples to NA and optionally interpolate these parts
Runs a PARAFAC analysis on EEM data
Importer function for Hitachi F-7000 txt files to be used with eem_read().
Plot a set of PARAFAC models to compare the single components
Remove Raman and Rayleigh scattering in fluorescence data
Upload PARAFAC models to openfluor.org
Calculating EEMqual which is an indicator of a PARAFAC model's quality
Combining extracted components of PARAFAC models
Calculate the leverage of each emission and excitation wavelength and each sample from a single PARAFAC model
Combine leverages into one data frame and add optional labels.
Create one table containing the PARAFAC models factors and optionally exporting it to csv or txt
Plot components from a PARAFAC model
Plot results from an SSC check
3D plots of PARAFAC components
Plot leverage of emission wavelengths, excitation wavelengths and samples.
Plot leverage of emission wavelengths, excitation wavelengths and samples.
Extract data from emission and excitation wavelengths of the components of a PARAFAC model (scaled B- and C-modes)
Reorder PARAFAC components
PARAFAC model, see vignette, non-negative constraints, normalised, outliers removed
Compensate for normalisation in C-modes
PARAFAC model, see vignette, non-negative constraints, normalised
Calculate the importance of each component.
Check SSCs between different models or initialisations of one model
Extracting components of a PARAFAC model
Extracting a list of sample names in each subsample from a splithalf analysis
Create a html report of a PARAFAC analysis
Rescale B and C modes of PARAFAC model
Write out PARAFAC components to submit to openfluor.org.
Plot correlations of components in samples
Extract EEM matrix for single components determined in the PARAFAC analysis
Calculating correlations between the component loadings in all samples (C-Modes).
Calculate a PARAFAC model similar to and using parafac.
Plot all components of PARAFAC models
Normalise 3-dimensional array in first and second dimension
Extracting TCC values from a splithalf analysis
PARAFAC model, see vignette, unconstrained
Caluclate Tucker's Congruence Coefficient of PARAFAC components
Reorders components of different PARAFAC models according to best fit (TCC)
Fits vs. components of PARAFAC models are plotted
Plot amount of each component in each sample as bar plot
Create table of PARAFAC components and (optionally) EEM peaks and indices as well as absorbance slope parameters.
Export samples in an EEM list to a single csv files
Calculate the combination of components giving the maximum of geometric mean of TCCs
PARAFAC model, see vignette, non-negative constraints
Calculate the shift-and shape-sensitive congruence (SSC) between two matrices
Running a Split-Half analysis on a PARAFAC model
Plot samples by means of whole sample, each single component and residuum
Calculate the shift-and shape-sensitive congruence (SSC) between model components
Plot results from a splithalf analysis
Calculate the leverage of each emission and excitation wavelength and each sample from a list of PARAFAC models
Calculate residual metrics from a PARAFAC model
EEM spectra plotted with ggplot2
result from PARAFAC split-half analysis, periodic data split
Calculate residuals of EEM data according to a certain model
Full join of a list of data frames.
PARAFAC model, see vignette, non-negative constraints, normalised, outliers removed, high accuarcy
Calculating slopes and slope ratios of a data frame of absorbance data.
Baseline correction for absorbance data
Multiply absorbance data according to the dilution and remove absorbance from samples where undiluted data is used.
Import EEMs from generic csv files.
Calculate the sample loadings for samples not involved in model building
Fit absorbance data to exponential curve. drm is used for the fitting process.
Add data of a PARAFAC model derived from multiway from EEMs
Data from an eemlist is transformed into an array
Converting EEM data from class eem to data.frame.
Reading absorbance data from txt and csv files.
Applying functions on EEMs
Importer function for generic csv files to be used with eem_read().
Create table how samples should be corrected because of dilution
Check for duplicate sample names