slide1 n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Predictor discovery in training set PowerPoint Presentation
Download Presentation
Predictor discovery in training set

Loading in 2 Seconds...

play fullscreen
1 / 12

Predictor discovery in training set - PowerPoint PPT Presentation


  • 76 Views
  • Uploaded on

Figure 1. Cluster analysis. DIGE analysis. 2. Prediction analysis of microarray (PAM). 1. 2d hierarchical clustering heatmap plotting. DIGE raw gel images SJIA (13 F, 13 Q) POLY (5 F, 5 Q). Predictor discovery in training set. Class prediction in testing set. 6. 7. 3.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Predictor discovery in training set' - freya-gaines


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1

Figure 1

Cluster analysis

DIGE analysis

2

Prediction analysis of microarray (PAM)

1

2d hierarchical

clustering

heatmap plotting

DIGE

raw gel images

SJIA (13 F, 13 Q)

POLY (5 F, 5 Q)

Predictor discovery

in training set

Class prediction

in testing set

6

7

3

Spot finding

spot alignment

feature extraction

Training set

SJIA (24 F, 14 Q)

POLY (15 F, 10 Q)

Testing set

SJIA (24 F, 14 Q)

POLY (15 F, 11 Q)

Mann Whitney

P < 10-5

10 protein

candidates

Normalization

manual review

8

Classifier

training

PAM

class prediction algorithm

7 feature

biomarker panel

4

Predictors of

4 ~ 12 features

889 discrete

spot features

Literature review

+ literature

candidates

- check antibody

availability

Ten-fold

cross-validation

Construct estimates of

predicted class probabilities

Manual review

Prospective

Study

N.D.

Discriminate

SJIA F

KD

FI

Classify

SJIA F vs Q

POLY F vs Q

MSMS ID

97 spots

Analysis of goodness

of class separation

5

12 ELISA assays

slide2

SJIA

POLY

F

Q

F

Q

Figure 2

slide3

SJIA

F

Q

Figure 3

slide4

SJIA

POLY

F

Q

F

Q

Figure 4

SAP

A2M

APOAIV

CFHR1

HP

ATIII

CRP

ATIII

HP

GSN

A2M

A2M

CFHR1

GSN

GSN

TTR

GSN

APOA1

A2M

APOA1

ATIII

APOA1

ATIII

APOA1

TTR

APOA1

APOA1

APOA1

APOA1

SAP

APOIV

APOIV

APOA1

HP

APOA1

CRP

APOA1

HP

MRP14

HP

HP

HP

HP

HP

HP

HP

HP

HP

HP

MRP8

MRP8

MRP8

MRP8

MRP14

SAA

SAA

SAA

SAA

SAA

SAA

slide5

Figure 5A

TRAINING

TESTING

POLY Q

POLY F

POLY Q

POLY F

slide6

SJIA F

SJIA Q

SJIA Q

Figure 5B

TRAINING

TESTING

SJIA F

slide7

Figure 6A

Goodness of class separation – D probability

POLY Training

POLY Testing

Feature#

4

5

7

8

12

4

5

7

8

12

slide8

Figure 6B

Goodness of class separation – D probability

SJIA Training

SJIA Testing

Feature#

4

5

6

7

8

9

12

4

5

6

7

8

9

12

slide9

SJIA F

SJIA Q

SJIA Q

Figure 7

TRAINING

TESTING

SJIA F

slide10

Figure 8

A

B

C

Training set

n = 38

Testing set

n = 38

SJIA

SJIA

  • Biomarker panel
  • of 7 members
  • HP
  • APO AI
  • A2M
  • SAP
  • CRP
  • MRP8/MRP14
  • SAA

Clinical

diagnosis

Clinical

diagnosis

F

Q

F

Q

24

14

24

14

n =

n =

PAM

PAM

Classified

as F

Classified

as F

18

5

21

4

Classified

as Q

Classified

as Q

6

9

3

10

75%

64%

88%

71%

Percent

Agreement

with clinical

diagnosis

+

-

Percent

Agreement

with clinical

diagnosis

+

-

71%

82%

Overall

P < 0.05

Overall

P < 0.001

slide11

SAP

MRP14

1

23

Figure 9

SJIA

F

KD

FI

Data set

n = 27

13

12

12

SJIA

F

NOT-SJIA

F

Clinical

diagnosis

13

24

n =

SAA

MRP8

Unsupervised

clustering

HP

Clustered

as SJIA F

10

Clustered

as NOT-SJIA F

3

CRP

77%

96%

-

Percent

Agreement

with clinical

diagnosis

+

APOA1

85%

Overall

P < 10-5

A2M