Hello,
I will be very obliged if someone can help me with this statistical R
problem:
I am trying to do a Pearson correlation on my datasets X, Y with
randomization test. My X and Y datasets are pairs.
1. I want to randomize (rearrange) only my X dataset per row ,while
keeping the my Y dataset as it is.
2. Then Calculate the correlation for this pair, and compare it to
your true value of correlation.
3. Repeat 2 and 3 maybe a 100 times
4. If your true p-value is greater than 95% of the random values,
then you can reject the null hypothesis at p<0.05.
I am stuck at the randomization step. I need some help in implementing
it the appropriate randomization step in my correlation.
Below is my incomplete code. I will be very obliged if someone could
help:
X <- read.table("X.txt",as.is=T,header=T,row.names=1)
Y <- read.table("Y.txt",as.is=T,header=T,row.names=1)
X.mat<- as.matrix(X)
Y.mat<- as.matrix(Y)
Corrs<- cor.test(X.mat[1,],Y.mat[1,],alternative =c("greater"),method=
c("pearson"))
Corrs.rand <- list()
for (i in 1:length(X.mat)){
for (j in 1:100){
# This doesnot seem to wrok correctly. How do I run sample function 100
times for the same row?
SNP.rand<- sample(SNP.mat[i,],56, replace = FALSE, prob = NULL)
Corrs.rand[[j]]<- cor.test(SNP.rand,CNV.mat[j,],alternative
=c("greater"),method= c("pearson"))
# need to calculate how many times my pvalue from true p-value> random
pvalue
}
}
X dataset:
#Probes
X10851
X12144
X12155
X11882
X10860
X12762
X12239
X12154
1
1
1
0
0
1
0
2
0
2
0
0
0
0
0
0
0
0
3
2
2
2
2
1
2
1
2
4
0
0
0
0
0
0
0
0
5
2
2
2
2
2
2
2
2
6
0
1
0
0
1
1
1
1
7
2
2
NaN
2
2
2
2
2
8
2
2
2
2
2
2
2
2
9
0
1
0
1
1
NaN
1
2
10
2
2
2
2
2
2
2
2
11
2
0
0
0
0
0
0
0
12
0
1
0
1
1
0
1
1
Y dataset:
Probes
X10851
X12144
X12155
X11882
X10860
X12762
X12239
X12154
1
793.0831
788.1814
867.8504
729.8321
816.852
805.2114
774.599
854.6384
2
12.8695
4.312894
10.69769
5.872213
13.793
9.394133
6.297553
9.307943
3
699.7792
826.9974
795.641
770.9376
806.1241
782.397
817.1075
859.7155
4
892.8217
869.0481
806.3387
812.0431
873.5565
794.4752
813.9587
814.8681
5
892.8217
869.0481
806.3387
812.0431
873.5565
794.4752
813.9587
814.8681
6
839.735
943.4456
950.7575
859.0208
894.246
853.5241
941.4842
913.0246
7
653.1272
751.5218
750.1758
737.3821
757.8486
758.2407
724.2186
770.8669
8
12.8695
4.312894
10.69769
5.872213
13.793
9.394133
6.297553
9.307943
9
839.735
943.4456
950.7575
859.0208
894.246
853.5241
941.4842
913.0246
10
653.1272
751.5218
750.1758
737.3821
757.8486
758.2407
724.2186
770.8669
11
653.1272
751.5218
750.1758
737.3821
757.8486
758.2407
724.2186
770.8669
12
839.735
943.4456
950.7575
859.0208
894.246
853.5241
941.4842
913.0246
Thanks in advance
Manisha
Mount Sinai School of Medicine
Icahn Medical Institute,
1425 Madison Avenue, Box 1498
NY-10029, NEW-YORK, USA
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
