Multivariate Data Analysis

Multivariate Data Analysis

Susan Holmes ?



Bio-X and Statistics

IMA Workshop, October, 2013

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you do not really understand something unless you can

explain it to your grandmother -- Albert Einstein

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you do not really understand something unless you can

explain it to your grandmother -- Albert Einstein

I am your grandmother .........

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What are multivariate data ?

Simplest format: matrices:

If we have measured 10,000 genes on hundreds of patients

and all the genes are independent, we can't do better than

analyze each gene's behavior by using histograms or box

plots, looking at the means, medians, variances and other `one

dimensional statistics'. However if some of the genes are

acting together, either that they are positively correlated or

that they inhibit each other, we will miss a lot of important

information by slicing the data up into those column vectors

and studying them separately. Thus important connections

between genes are only available to us if we consider the

data as a whole. We start by giving a few examples of data

that we encounter.

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?

Athletes, performances in the decathlon.

100 long poid haut 400 110 disq perc jave 15

1 11.25 7.43 15.48 2.27 48.90 15.13 49.28 4.7 61.32

2 10.87 7.45 14.97 1.97 47.71 14.46 44.36 5.1 61.76

3 11.18 7.44 14.20 1.97 48.29 14.81 43.66 5.2 64.16

4 10.62 7.38 15.02 2.03 49.06 14.72 44.80 4.9 64.04

5 11.02 7.43 12.92 1.97 47.44 14.40 41.20 5.2 57.46

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Clinical measurements (diabetes data).

1

3

5

7

9

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relwt glufast glutest steady insulin Group

0.81

80

356

124

55

3

0.94

105

319

143

105

3

1.00

90

323

240

143

3

0.91

100

350

221

119

3

0.99

97

379

142

98

3

OTU read counts:

EKCM1.489478

EKCM7.489464

EKBM2.489466

469478 208196 378462 265971 570812

0

0

2

0

0

0

0

2

0

2

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0

0 . .. ..12

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