ASD The Unscrambler®

The Unscrambler^® software from Camo Software is a complete Multivariate Analysis and Experimental Design software solution, available with powerful methods including PCA, Multivariate Curve Resolution (MCR), 3-Way PLS Regression, PLS Regression, Clustering (K-Means), SIMCA and PLSDA Classification etc.

The Unscrambler Key Features

Analysis Methods

Descriptive statistics (Mean, Box-Plot, skewness, kurtosis, Standard Deviation, correlation matrix)

Principal Component Analysis (PCA)

Multivariate Curve Resolution (MCR)

Prediction from PLS-R, PCR and 3-way PLSR models

Regression (MLR, PLS-R, PCR, 3-way PLS-R)

Clustering (K-Means)

Classification (PLS-DA, SIMCA)

Validation options: Leverage Correction, Cross-Validation (freely choose number of samples per segment), Test Set

Variable Scaling options: Scaling is free on each variable. Suggested options: Constant, Auto-scaling, Passify

Interaction and Square terms can be included in MLR, PCR, PCA and PLS-R models

ANOVA and Response Surface ANOVA

Smart Tools for Analysis

Automatic detection of significant X-variables in PLS-R and PCR

Model Stability in PCR, PCA and PLS-R

Automatic outlier detection in PCA, MLR, PLS-, PCR and Prediction

Message list of recommendations in MCR modeling

Interactive analysis:

Mark samples and/or variables on plots

Recalculate without or with marked samples or variables

Recalculate with pacified unmarked or marked variables

Extract Data from unmarked or marked

Interactive help

Tutorial exercises guiding users through the use of all the unscrambler modeling techniques in application examples

Automatic Pretreatments in prediction and classification

Design of Experiments

Factorial (F) and Fractional Factorial (FF) designs

Plackett-Burman (PB) designs

Mixture designs (Axial, Simplex-Lattice, Simplex-Centroid)

D-Optimal designs of mixtures and non-mixtures

Plots of main and interaction effects; Response Surface Modeling (RSM)

Design Wizard: Takes users through the stages of building a design

Third order variable interaction

Central Composite Designs (CCD)

Box Behnken (BB) designs

Data Pretreatments

Smoothing: Moving Average, Median filter, Savitzky Golay, Gaussian filter

Normalize: Area, Unit Vector, Mean, Range, Peak, Maximum

Spectroscopic conversions: absorbance/reflectance, reflectance/Kubelka-Munk, wave number/ nanometers

Multiplicative Signal Correction (MSC) and Extended MSC (EMSC)

Noise

Derivatives: Norris-Gap, Savitzky Golay and Gap-Segment

Baseline offset and Linear Baseline correction

Standard Normal Variate (SNV)

Mean centering, standard deviation scaling

User-Defined pretreatments (programmed for example in Matlab or C++ and utilized in the Unscrambler as a dll)

The Result Viewer

More than 100 pre-defined plots (Scores, Loading weights, Correlation Loadings, Loadings, Stability Plot, Bi-plot, Variances, RMSE, Regression coefficients, Leverages, Predicted vs. Measured, Residuals, Response Surface…)

Live rotation of 3D plots

PC Navigation tool: navigate along model components in a single click

A number of plot options: Sample grouping with symbols or colors; Insert text; Remove grid; Display plot as Line/Bars/Accumulated bars…

Spreadsheet Editor

No size limit

3D and 2D tables supported

Discrete, continuous and mixture variables supported

Sample and variable names of up to 49 characters

Sort samples/Sort Variables

Transpose

Mathematical array manipulation

Fill missing values

Undo/Redo functionality

Raw data plots (Line, 2D scatter, 3D scatter, Histogram, Matrix, Normal probability, Matrix 3D)

Set Editor: allows to work freely either on the whole table or on a selection of samples and/or variables

Interactions with Other Software

Drag 'n' drop values, variable names and sample names from Excel to The Unscrambler

Copy/Paste data or plots to Microsoft Office applications

Data import of 3D and 2D data tables with over 20 file formats supported: ASCII, spreadsheet software (Excel, Lotus), statistical software (NSAS, Matlab) and instrument software: JCAMP-DX, Tracker (Foss), APC, Grams (Thermo Electron), MVACDF, Indico (Analytical Spectral Devices), CLASS-PA and SpectrOn (Guided-Wave), F3D (Hitachi), BFF3 (Brimrose)

User-Defined Import: enables importing any file format using a preprogrammed DLL

Data export in different formats (Matlab, ASCII, JCAMP-DX…)

Model export in different formats (ASCII, NSAS, Tracker, Vision)

21 CFR Part 11 Compliant

Password protected Login, with password expiration after 70 days

Secure electronic signatures

The user name, time, date and software version used to generate data and model files are registered

Details from the instrument source file are passed on into the Unscrambler data file under importation

Locked data sets cannot be edited

The source data set’s name and path are recorded in the resulting model file

The source data set’s transformations are recorded in the resulting model file

The complete and detailed model settings are recorded in the resulting model file

Printed plots contain time, date, file name, user initials and software name

All formatting operations on the data set are recorded in the Log trail

All computations performed on the data set are recorded in the Log trail

All transformations performed on the data set are recorded in the Log trail

PCA Projection

The potential to carry out prediction with a PCA model. Samples are projected onto a saved PCA model. Relevant statistics and plots are updated with new projected samples. Auto-pretreatment is also supported.

De-trending

De-trending (DT) is a transformation which aims at removing non-linear trends in spectroscopic data. Standard normal variate (SNV) and DT in combination decrease multi co-linearity, curvature and baseline shift. These transformations are applied to individual spectra and are distinct from other transformations which function at each wavelength in a given set of spectra. SNV is already implemented in The Unscrambler. This pre-treatment corrects shifts in data on the y-axis. However, SNV corrected data could still be affected by the baseline curvature. To remove this effect, DT is carried out by fitting a second-order (or higher degree) polynomial to the spectral data. This is then followed by subtracting this curve from the spectrum in order to provide the transformed result.

SPA / SPG (Omnic), BSW (Varian) File Import

SPA/ SPG (Omnic), BSW (Varian) File Import Projection are supported.

Sample Grouping on Line Plots

Sample grouping allows effortless distinguishing between classes or groups of samples plotted directly from the Unscrambler editor, specifically useful for spectroscopic users.

Easy Activation of Pre-treatment Steps

Auto-pre-treatment registration functionality made simple to use.

MLR Prediction

The philosophy of The Unscrambler is fixated on projection methods, and specifically PLS regression. MLR prediction is presently available in Unscrambler Predictor. MLR is in use by (but not limited to) spectroscopic users.

File Merge (PCA, PCR, PLS1, PLS2, MLR, MSC, EMSC)

The Unscrambler file system comprises of a set of files to represent the model and data file. When a model file is saved in The Unscrambler, it develops five files with extensions of *.xxD, *.xxP, *.xxL, *.xxT, *.xxW. The main information of the file is in *.xxD. Other information about the model like log information, notes and history of the file is circulated across the sub files. File merge option presently merges all the files into one single file. This single file comprises of all the sub files and also the EMSC and MSC model files if the pre-treatments are used in the model file.

3^rd Order Variable Interactions

Third order variable interactions comprise of interactions between three design parameters (A*B*C), combined effects (A2*B) and cubic terms of the design variables (A3).

R-square

R² (read: R-square) is presently available in addition to R in the statistics box in the predicted vs measured plot.

Varimax Rotation

The Unscrambler 9.8 provides four different rotations: Varimax, Equimax, Quartimax and Parsimax. These rotations are to be applied after PCA analysis.