the correp packagefor r - portalukc – universitätsinstitut für klinische chemie data preparation...
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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
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UKC – Universitätsinstitut für Klinische Chemie
Prologue –DIRECT results: weight loss and altered lipids
Weight loss [kg] Total Cholesterol/HDL
months months
What we got:
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Samples of 90male participants (28/28/34) at 0, 6, and 24 months (n=270).
UKC – Universitätsinstitut für Klinische Chemie
DIRECT – 2‐year diet affecting cholesterol metabolism?
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UKC – Universitätsinstitut für Klinische Chemie
DIRECT – What about covariates (e.g. BMI or HOMA‐IR)?
That‘s it?
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That s it?
UKC – Universitätsinstitut für Klinische Chemie
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?
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single man?
UKC – Universitätsinstitut für Klinische Chemie
DIRECT – remind: n=90 at 0, 6, and 24 months.
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What if… …timepoints are only replicates?
UKC – Universitätsinstitut für Klinische Chemie
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
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UKC – Universitätsinstitut für Klinische Chemie
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‘ )
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UKC – Universitätsinstitut für Klinische Chemie
Revision #2:l dd h lPlease add the P values
for the correlations.
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UKC – Universitätsinstitut für Klinische Chemie
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
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UKC – Universitätsinstitut für Klinische Chemie
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UKC – Universitätsinstitut für Klinische Chemie
DIRECT: Finally…..
Am J Clin Nutr. 2011 Nov;94(5):1189‐95. Epub 2011 Sep 21.
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Am J Clin Nutr. 2011 Nov;94(5):1189 95. Epub 2011 Sep 21.PMID: 21940598 (Free Article)