Tang Lab In the Department of Genetics

People: PCA of Lab Members

example_image
An example of a PCA graph based on genetic
information from European individuals

PCA, or "principle component analysis," is a method of translating correlated variables into uncorrelated variables. The first component is defined to explain as much of the variability in the data as possible, and the second component explains as much variability in the data as possible, given that it is orthogonal to the first component. PCA is used in genetics (and many other fields) to discern the internal structure of a given data set, and can give insights into which data are most similar to which other data in that given data set. Being the geeks that we are, we have applied this method to our lab members. Which members are most similar to each other, given their responses to a series of questions?

The "data" used in our lab PCA
Question Hua Sandra Sophie Emily Yoohna

Food:
A. chili pepper hot
or
B. saltine bland

A
B

A

A
A

Personality:
A. social butterfly
or
B. homebody

B
A
B
A
B

Sleep:
A. night owl
or
B. early bird

B
B
B
B
A

Caffeine intake:
A. coffee mug
or
B. tea cup

B
A
A
B
A

Driving:
A. Speed demon
or
B. granny

B
A
B
B
B

Music:
A. Mozart
or
B. Grateful Dead

A
B
B
A
A

Adventure level:
A. Skydiver
or
B. Sunday stroll

B
B
A
A
B

Lactose tolerance:
A. Milk lover
or
B. Milkshake nightmares

B

A

B

A

A

Reading:
A. Fiction
or
B. Non-Fiction

A
A
A
A
A
Age-old question:
A. Nature
or
B. Nurture
A
A
A
A
A
Pet preference:
A. Cat
or
B. Dog
A
A
A
B
B

Fav Flav:
A. Vanilla
or
B. Chocolate

B
A
A
A
B

pca

  PC1 PC2 PC3 PC4 PC5
Hua 0.50628871 -0.38581762 -0.27591035 0.71351799 -0.09788801
Sandra -0.63581058 -0.03319705 -0.07196222 0.30894627 -0.70286308
Sophie 0.01194515 -0.80635596 -0.16548641 -0.53465984 -0.19078910
Emily 0.28266227 -0.12358482 0.89273054 0.03298822 -0.32676108
Yoonha 0.50928971 0.42960398 -0.30715038 -0.32938566 -0.59433000

 

PC1 PC2 PC3 PC4 PC5
Food -2.1858632 9.736781e-01 0.07309607 0.11913031 0.323137522
Personality 1.0824695 -4.755911e-01 -1.25550364 -0.64143008 -0.008080163
Sleep -0.5677086 -1.594314e+00 0.91668423 0.64568855 -0.874276886
Caffeine 0.6408690 -7.545997e-05 1.37002687 1.06186240 0.848808481
Driving 1.6298426 -7.149121e-01 0.47326161 -0.57754868 -0.640850269
Music -2.1631989 -5.562748e-01 -0.24089233 -0.89531542 -0.038859343
Adventure -0.1714367 9.900759e-01 -1.08086949 0.97128753 -1.007171799
Milk 0.1161602 -1.290707e+00 -0.67272677 -0.01646474 1.119581721
Pet 0.5590611 1.613759e+00 1.35843869 -1.04022551 -0.076205967
Flavor 1.0598051 1.054362e+00 -0.94151525 0.37301565 0.353916702

 

 

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