Dedicated Aquaphotomics-Software

R-Package „aquap2“General Introduction and Workshop
Bernhard Pollner & Zoltan Kovacs

Aquaphotomics: Understanding Water in Biology
at the 2nd International Aquaphotomics Symposium
26.-29. November 2016, Kobe, Japan

Outline & Schedule≤ 40 minutes:• general introduction - basic concept• aquap2 helps in:• experiment-design,• data import and organization• data analysis and visualization~ 2.25 hours:• practical use & „hands-on“ workshop• using training datasets• just bring your laptop!

How it all Started…

Why R-Project ?

• high level programming language• open source - freeware !
• cross-platform• powerful - extendable• possible: something really new• widely used in academia

MVA package withadditional focus on Aquaphotomics„aquap2“Package „aquap2“• still in beta
• yet already powerful and extremely flexible & versatile
Main Advantage• can dramatically speed up analysis time
• highly repetitive tasks get completely scriptable, i.e. automatedMVA Methods
Already Implemented• Data pre-treatment• smoothing, 2nd derivative, SNV, MSC, EMSC, deTrend,gap derivative, …

• PCA; SIMCA; PLSR
• Aquagram (classic & extended)
In the Pipeline• PLS-DA; ANN; SVM; ICAKey Features IExperiment Design• truly randomize samples• facilitates time resolved experiments
Data Import & Organization• import of metadata: class.- and numerical variables• import of spectral data
• consistent coloring• align environmental data (T, rH) to timestamp on spectra• add custom, device-specific noise to dataset
Data Analysis & Visualization• Bootstrapped Aquagram: custom temperature calibration data
• User-defined splitting of dataset by wavelength or any class-variable• Highly flexible input and control system

Key Features II: User-defined splitting of dataset

Split by „C_Time“

Key Features II: User-defined splitting of dataset

Key Features II: User-defined splitting of dataset

Separate Analysis andVisualization

Split by „C_Group“

Key Features II: User-defined splitting of dataset

Key Features II: User-defined splitting of dataset

Separate Analysis andVisualization

Separate Analysis andVisualization

Key Features III: Input & Controlset up once,
modify rarely

Global Settingsexperiments obtain parametersfrom global settings

modifyexperiment-specificExperiment-wise Settings
Code-based, programmatic
overriding of parametersmodify often duringexploratory analysis

Manual, user-defined Input
when calling Functions

3 levels of control• flexible, highly customizable• global settings: change input globally in a single, central file („settings.r“)• experiment-wise settings: the specific metadata and analysis procedure file for each experiment.
• code-based overriding of parameters: Enables programmatic, i.e. scriptable modification of input-parameters.

Summary - Main Advantages• fully scriptable analysis routines• consisting of (user´s) custom
code, and• easy-to-use analysis modules• same analysis of an exact

repetition of a previous
experiment can so be done in a
few seconds - just by plugging
new data into the old (copied)
analysis routine

DatasetAAnalysis
Routineev
SaDataset
B

Result!
!
emiTAnalysis
RoutineThink - Copy&Paste - Enjoy

ResultNow: Hands-On aquap2