i ndependent c omponents a nalysis i ndependent c omponents a nalysis applications of ica douglas n....

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INDEPENDENT COMPONENTS INDEPENDENT COMPONENTS ANALYSIS ANALYSIS Applications of ICA Douglas N. Rutledge , Delphine Jouan-Rimbaud Bouveresse [email protected] [email protected]

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Page 1: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

INDEPENDENT COMPONENTS ANALYSIS INDEPENDENT COMPONENTS ANALYSIS

Applications of ICA

Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse

[email protected] [email protected]

Page 2: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

50010001500200025003000350040000

10

20

30

40

50

60

70

80

90

cm-1

Information Hidden in MIR Spectra

Source : R.Aries, D. Lidiard, R. Spragg, Spectrosc. Internat., 2(3) 41-44

Page 3: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA on 100 Mid-Infrared spectra

• Samples : a single polystyrene film

• Mid-IR spectra taken at end of production line

• Acquired from 4000cm-1 to 400cm-1, at 1 cm-1

• Pre-treatment of spectra :- normalised between 0 and 1- neither centred nor standardised

Page 4: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

PC2 CO2 & H2O

Results of a PCA on the polystyrene MIR data

Page 5: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

PC6

Interferogram & derivativePC5

Interferogram & derivative

Page 6: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

PC5-PC6 Scores Plot

-0.1

0

0.1

0.2

0.3

0.4

-0.2 0 0.2 0.4

PC5

PC

6

61

Page 7: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

IC2/7 signal looks like water vapour spectrum

Due to variations in moisture content of air

Page 8: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

IC3/7 signal looks like spectrum of CO2

Due to variations in CO2 content of air

Page 9: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

IC4/7 signal looks like beats of a simple interferogram

Due to variations in optical path of polystyrene sample ?

Page 10: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

IC7/7 signal looks like first derivative of average MIR spectrum

Due to one spectrometer (N°61) being badly adjusted (frequency shift)

Page 11: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Elimination of artifacts

Monitoring changes in oils during heating using 3-D Fluorescence Spectroscopy

Page 12: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Rayleigh scattering

Ramanscattering

ex

(nm)

em (

nm)

280 300 320 340 360 380 400 420 440

300

350

400

450

500

550

600

650

700

3-D Fluorescence Spectra of Oils during Heating

Page 13: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ex

(nm)

em (

nm)

IC1

280 300 320 340 360 380 400 420 440

300

350

400

450

500

550

600

650

700

IC1 = Rayleigh + Raman

Page 14: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ex

(nm)

em (

nm)

IC2

280 300 320 340 360 380 400 420 440

300

350

400

450

500

550

600

650

700

IC2 = Polyphenols

Page 15: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ex (nm)

em (

nm)

IC3

280 300 320 340 360 380 400 420 440

300

350

400

450

500

550

600

650

700

IC3 = Chlorophyll…

Page 16: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Antioxydant influence of catechin on rats after hyperlipidic diets, monitored using a LC-MS based metabolomic

approach

Page 17: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

The data • Samples• Male Wistar rats (n = 8/group) fed for 6 weeks normo- (5% diet w/w) or hyper- lipidic (15 and 25%) diets (CT05 / HF15 / HF25)

• With or without catechin supplementation (0.2% w/w) (NP / PP) (polyphenolic antioxidant - helps prevent inflammatory and coronary diseases)

• Urines collected 17 and 38 days after diets were given (T17 / T38)

• Technique• Analysed by mass spectrometry on a LC-QToF (m/z 100-1000; positive ionization)(HPLC Alliance 2695, Symmetry® RP18 column, Micromass Qtof-Micro / Waters)

• Pretreatment• Intensities of peaks transformed to log(X+1)

• Variables sorted in order of decreasing variance(later as function of Retention Time)

Page 18: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

100

200

300

400

500

600

700

800

900

12

34

56

78

910

0

5

Log(raw LC-MS data)

Page 19: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Log(raw LC-MS data)

Page 20: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Independent Components Analysis

Extract “pure signals” from observed mixtures

- “pure signals” => “Loadings”

- “proportions” of “pure signals” to mixtures = “Scores”

Page 21: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

2 4 6 8 10 12 14 16 18 20 22 24

1.51.61.71.81.9

IC1 (Fat)

5 10 15 20 25 30 35

1.51.61.71.81.9

IC1 (Catechine)

5 10 15 20 25 30 35

1.51.61.71.81.9

IC1 (Days)

ICA on Log(Data)

Page 22: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA on Log(Data)

2 4 6 8 10 12 14 16 18 20 22 24

-1.5

-1

-0.5

IC2 (Fat)

5 10 15 20 25 30 35

-1.5

-1

-0.5

IC2 (Catechine)

5 10 15 20 25 30 35

-1.5

-1

-0.5

IC2 (Days)

Page 23: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

2 4 6 8 10 12 14 16 18 20 22 24

-1

-0.5

0IC3 (Fat)

5 10 15 20 25 30 35

-1

-0.5

0IC3 (Catechine)

5 10 15 20 25 30 35

-1

-0.5

0IC3 (Days)

2 4 6 8 10 12 14 16 18 20 22 24

-1

-0.5

0IC3 (Fat)

5 10 15 20 25 30 35

-1

-0.5

0IC3 (Catechine)

5 10 15 20 25 30 35

-1

-0.5

0IC3 (Days)

ICA on Log(Data)

Page 24: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

2 4 6 8 10 12 14 16 18 20 22 24

-0.8-0.6-0.4-0.2

00.20.4

IC4 (Fat)

5 10 15 20 25 30 35

-0.8-0.6-0.4-0.2

00.20.4

IC4 (Catechine)

5 10 15 20 25 30 35

-0.8-0.6-0.4-0.2

00.20.4

IC4 (Days)

2 4 6 8 10 12 14 16 18 20 22 24

-0.8-0.6-0.4-0.2

00.20.4

IC4 (Fat)

5 10 15 20 25 30 35

-0.8-0.6-0.4-0.2

00.20.4

IC4 (Catechine)

5 10 15 20 25 30 35

-0.8-0.6-0.4-0.2

00.20.4

IC4 (Days)

ICA on Log(Data)

Page 25: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

2 4 6 8 10 12 14 16 18 20 22 24

-1

-0.5

0

IC5 (Fat)

5 10 15 20 25 30 35

-1

-0.5

0

IC5 (Catechine)

5 10 15 20 25 30 35

-1

-0.5

0

IC5 (Days)

2 4 6 8 10 12 14 16 18 20 22 24

-1

-0.5

0

IC5 (Fat)

5 10 15 20 25 30 35

-1

-0.5

0

IC5 (Catechine)

5 10 15 20 25 30 35

-1

-0.5

0

IC5 (Days)

ICA on Log(Data)

Page 26: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

2 4 6 8 10 12 14 16 18 20 22 24

-1

-0.5

0

IC5 (Fat)

5 10 15 20 25 30 35

-1

-0.5

0

IC5 (Catechine)

5 10 15 20 25 30 35

-1

-0.5

0

IC5 (Days)

2 4 6 8 10 12 14 16 18 20 22 24

-0.8-0.6-0.4-0.2

00.20.4

IC6 (Fat)

5 10 15 20 25 30 35

-0.8-0.6-0.4-0.2

00.20.4

IC6 (Catechine)

5 10 15 20 25 30 35

-0.8-0.6-0.4-0.2

00.20.4

IC6 (Days)

ICA on Log(Data)

Page 27: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

200

400600

800

24

68

10

-4

-2

0

2

IC2

IC2 “Loadings”

Page 28: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

200

400600

800

24

68

10

-6

-4

-2

0

2

IC3

IC3 “Loadings”

Page 29: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

200

400600

800

24

68

10

-5

0

5

IC5

IC5 “Loadings”

Page 30: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Mid-Infrared analysis of edible oilsheated at 190° for 3 hours

Page 31: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA applied to Mid-Infrared spectra

180 spectra acquired every 3 minutes over 3 hours during flat heating at 190°C

Page 32: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

PCA Loadings

Page 33: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

PCA Scores

Page 34: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA Signals

Page 35: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA Scores

Page 36: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Mid-IR spectrum of CO2

Page 37: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Scores of samples on IC9 as a function of heating time

Page 38: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Mid-IR spectrum cis-trans isomerisation

Page 39: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Scores of samples on IC2 as a function of heating time

Page 40: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA applied to Raman hyperspectral images

Hyperspectral images acquired for an authentic and a suspect pharmaceutical pill

M Boiret, D N Rutledge, N Gorretta, Y-M Ginot, J-M RogerUtilisation de la microscopie Raman et des methodes chimiometriques pour la detection de comprimes contrefaits, SpectrAnalyse, 2014, in press

Page 41: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

Images collected using a PerkinElmer RS400 system

Microscope coupled to spectrophotometer with 785nm 400mW laser

CCD sensor (Charge-Coupled Device)

Sample on a motorized stage with a pitch of 50 microns

Raman spectra acquired from 3200cm -1 to 100cm -1 Spectral resolution 2 cm -1

26 000 spectra on a surface of about 8mm * 8mm

Page 42: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA_by_Blocks applied to authentic and suspect pills

2 4 6 8 10 12 14

0.3

0.4

0.5

0.6

0.7

0.8

0.9

ICs

Low

est

Corr

ela

tions

Comprimé référence

Comprimé suspect

Page 43: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA Proportions

200 400 600 800 1000 1200 1400 1600 18000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Raman shift (cm-1)

Rel

. In

t.

Pure API

Signal 1

200 400 600 800 1000 1200 1400 1600 18000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Raman shift (cm-1)

Rel

. In

t.

Pure Excipient 1

Signal 2

200 400 600 800 1000 1200 1400 1600 18000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Raman shift (cm-1)

Rel

. In

t.

Pure excipient 3

Signal 3

ICA Signals& Reference spectra

R=0.99

R=0.99

R=0.98

Authentic pharmaceutical pill

Page 44: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

200 400 600 800 1000 1200 1400 1600 1800

0

1

2

3

4

5

6

Raman shift (cm-1)

Int.

S2

200 400 600 800 1000 1200 1400 1600 1800

0

1

2

3

4

5

6

7

8

9

10

Raman shift (cm-1)

Int.

S1

ICA Proportions ICA Signals

Suspect pharmaceutical pill

Page 45: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA Signals& Reference spectrum

(Metformine)

Suspect pharmaceutical pill

Compare ICA signals with spectral database

200 400 600 800 1000 1200 1400 1600 18000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Raman shift (cm-1)

Rel

. In

t.

Signal 1

Metformine

200 400 600 800 1000 1200 1400 1600 18000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Raman shift (cm-1)

Rel

. In

t.

Signal 2

Avicel

ICA Signals& Reference spectrum

(Avicel)

R=0.96R=0.99

Page 46: I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse douglas.rutledge@agroparistech.frdouglas.rutledge@agroparistech.fr

ICA can be applied to data usually analysed using PCA

Contributions of variables are easier to interpret

CONCLUSION