the correp packagefor r - portalukc – universitätsinstitut für klinische chemie data preparation...

The CORREP package for R

multivariate correlation estimation for replicated data

… and an ‘unusual’ application

http://cran.r‐project.org/web/packages/CORREP

UKC – Universitätsinstitut für Klinische Chemie

Prologue – the DIRECT study:

The DIRECT st dThe DIRECT study:

• 2‐year trial

• Enrollment 2004

• 322 participants

• 3 different diets

Closed environment

→ high compliance→ g p

CORREP – multivariate correlation estimation 2


Prologue –DIRECT results: weight loss and altered lipids

Weight loss [kg] Total Cholesterol/HDL

months months

What we got:


Samples of 90male participants (28/28/34) at 0, 6, and 24 months (n=270).


DIRECT – 2‐year diet affecting cholesterol metabolism?



DIRECT – What about covariates (e.g. BMI or HOMA‐IR)?

That‘s it?


That s it?


DIRECT – What the reviewers said…

4. Statistics: I am suspicious of the data for correlations described as ‘over all time points’. […] It would not be correct to introduce repeated measurements fromintroduce repeated measurements from individual subjects as independent measurements.measurements.

16. Figure 4. Is each man represented only once? If not, does the Kendall’s test adjust for multiple contributions by a single man?


single man?


DIRECT – remind: n=90 at 0, 6, and 24 months.


What if… …timepoints are only replicates?


Data preparationd <- as.matrix(Datenmatrix) d0 <- t(d)

p p

## This step is to make the std.-deviation of each replicate equals to 1## so that we can model the covariance matrix as correlation matrix.d0.std <- apply(d0, 1, function(x) x/sd(x))

patientsreplicates



Computation of the correlation matrix M

M < cor balance(t(d0 std) m=3 G=4) # Computation of MM <- cor.balance(t(d0.std), m=3, G=4) # Computation of M

balance: equal number of replicates assumed

m: number of replicates per ‚gene‘

G: number of different ‚genes‘ (e.g. ‚BMI‘ or ‚LaCh‘ )



Revision #2:l dd h lPlease add the P values

for the correlations.



Computation of the LR‐testp

#Select rows for gene 1 and gene 2g <-d0.std[,c(1,2,3,4,5,6)]g < d0.std[,c(1,2,3,4,5,6)]

#Perform the LR-test (m: number of replicates)cor.LRtest(t(g),m1=3,m2=3)( (g), , )

# Example: Result for BMI-LaChpcor.LRtest(t(g),m1=3,m2=3)[1] 4.861361e-06



DIRECT: Finally…..

Am J Clin Nutr. 2011 Nov;94(5):1189‐95. Epub 2011 Sep 21.


Am J Clin Nutr. 2011 Nov;94(5):1189 95. Epub 2011 Sep 21.PMID: 21940598 (Free Article)

the correp packagefor r - portalukc – universitätsinstitut für klinische chemie data preparation...

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