Mercurial > repos > jasonxu > matrixeqtl
comparison MatrixEQTL/man/modelANOVA.Rd @ 0:cd4c8e4a4b5b draft
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author | jasonxu |
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date | Fri, 12 Mar 2021 08:12:46 +0000 |
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1 \name{modelANOVA} | |
2 \alias{modelANOVA} | |
3 \docType{data} | |
4 \title{ | |
5 Constant for \code{\link{Matrix_eQTL_engine}}. | |
6 } | |
7 \description{ | |
8 Set parameter \code{useModel = modelANOVA} in the call of \code{\link{Matrix_eQTL_main}} to indicate that the genotype should be treated as a categorical variable. | |
9 } | |
10 \note{ | |
11 By default, the number of ANOVA categories is fixed to be 3. | |
12 | |
13 To set it to a different number (say, 4) use the following command: | |
14 | |
15 \code{options(MatrixEQTL.ANOVA.categories=4)} | |
16 | |
17 To check the current settings run: | |
18 | |
19 \code{getOption('MatrixEQTL.ANOVA.categories', 3);} | |
20 } | |
21 \examples{ | |
22 library('MatrixEQTL') | |
23 | |
24 # Number of columns (samples) | |
25 n = 100; | |
26 | |
27 # Number of covariates | |
28 nc = 10; | |
29 | |
30 # Generate the standard deviation of the noise | |
31 noise.std = 0.1 + rnorm(n)^2; | |
32 | |
33 # Generate the covariates | |
34 cvrt.mat = 2 + matrix(rnorm(n*nc), ncol = nc); | |
35 | |
36 # Generate the vectors with single genotype and expression variables | |
37 snps.mat = floor(runif(n, min = 0, max = 3)); | |
38 gene.mat = 1 + (snps.mat==1) + cvrt.mat \%*\% rnorm(nc) + rnorm(n) * noise.std; | |
39 | |
40 # Create 3 SlicedData objects for the analysis | |
41 snps1 = SlicedData$new( matrix( snps.mat, nrow = 1 ) ); | |
42 gene1 = SlicedData$new( matrix( gene.mat, nrow = 1 ) ); | |
43 cvrt1 = SlicedData$new( t(cvrt.mat) ); | |
44 | |
45 # name of temporary output file | |
46 filename = tempfile(); | |
47 | |
48 snps1 | |
49 gene1 | |
50 | |
51 # Call the main analysis function | |
52 me = Matrix_eQTL_main( | |
53 snps = snps1, | |
54 gene = gene1, | |
55 cvrt = cvrt1, | |
56 output_file_name = filename, | |
57 pvOutputThreshold = 1, | |
58 useModel = modelANOVA, | |
59 errorCovariance = diag(noise.std^2), | |
60 verbose = TRUE, | |
61 pvalue.hist = FALSE ); | |
62 # remove the output file | |
63 unlink( filename ); | |
64 | |
65 # Pull Matrix eQTL results - t-statistic and p-value | |
66 | |
67 fstat = me$all$eqtls$statistic; | |
68 pvalue = me$all$eqtls$pvalue; | |
69 rez = c( Fstat = fstat, pvalue = pvalue) | |
70 # And compare to those from ANOVA in R | |
71 { | |
72 cat('\n\n Matrix eQTL: \n'); | |
73 print(rez); | |
74 cat('\n R anova(lm()) output: \n') | |
75 lmodel = lm( gene.mat ~ cvrt.mat + factor(snps.mat), weights = 1/noise.std^2 ); | |
76 lmout = anova( lmodel )[2, 4:5]; | |
77 print( lmout ) | |
78 } | |
79 | |
80 # Results from Matrix eQTL and 'lm' must agree | |
81 stopifnot(all.equal(lmout, rez, check.attributes=FALSE)) | |
82 } | |
83 \references{ | |
84 The package website: \url{http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/} | |
85 } | |
86 \seealso{ | |
87 See \code{\link{Matrix_eQTL_engine}} for reference and sample code. | |
88 } |