Mercurial > repos > jasonxu > matrixeqtl
comparison MatrixEQTL/demo/b.cvrt.r @ 3:ae74f8fb3aef draft
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author | jasonxu |
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date | Fri, 12 Mar 2021 08:20:57 +0000 |
parents | cd4c8e4a4b5b |
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2:5fafba5359eb | 3:ae74f8fb3aef |
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1 library("MatrixEQTL"); | |
2 | |
3 # Number of columns (samples) | |
4 n = 100; | |
5 | |
6 # Number of covariates | |
7 nc = 10; | |
8 | |
9 | |
10 | |
11 | |
12 # Generate the covariates | |
13 cvrt.mat = 2 + matrix(rnorm(n*nc), ncol = nc); | |
14 | |
15 # Generate the vectors with genotype and expression variables | |
16 snps.mat = cvrt.mat %*% rnorm(nc) + rnorm(n); | |
17 gene.mat = cvrt.mat %*% rnorm(nc) + rnorm(n) + 0.5 * snps.mat + 1; | |
18 | |
19 # Create 3 SlicedData objects for the analysis | |
20 snps1 = SlicedData$new( matrix( snps.mat, nrow = 1 ) ); | |
21 gene1 = SlicedData$new( matrix( gene.mat, nrow = 1 ) ); | |
22 cvrt1 = SlicedData$new( t(cvrt.mat) ); | |
23 | |
24 # Produce no output files | |
25 filename = NULL; # tempfile() | |
26 | |
27 # Call the main analysis function | |
28 me = Matrix_eQTL_main( | |
29 snps = snps1, | |
30 gene = gene1, | |
31 cvrt = cvrt1, | |
32 output_file_name = filename, | |
33 pvOutputThreshold = 1, | |
34 useModel = modelLINEAR, | |
35 errorCovariance = numeric(), | |
36 verbose = TRUE, | |
37 pvalue.hist = FALSE ); | |
38 | |
39 # Pull Matrix eQTL results - t-statistic and p-value | |
40 beta = me$all$eqtls$beta; | |
41 tstat = me$all$eqtls$statistic; | |
42 pvalue = me$all$eqtls$pvalue; | |
43 rez = c(beta = beta, tstat = tstat, pvalue = pvalue); | |
44 # And compare to those from the linear regression in R | |
45 { | |
46 cat("\n\n Matrix eQTL: \n"); | |
47 print(rez); | |
48 cat("\n R summary(lm()) output: \n"); | |
49 lmdl = lm( gene.mat ~ snps.mat + cvrt.mat ); | |
50 | |
51 lmout = summary(lmdl)$coefficients[2,c("Estimate","t value","Pr(>|t|)")]; | |
52 print( lmout ); | |
53 } | |
54 | |
55 # Results from Matrix eQTL and "lm" must agree | |
56 stopifnot(all.equal(lmout, rez, check.attributes=FALSE)); |