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1 # Matrix eQTL by Andrey A. Shabalin
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2 # http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/
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3 #
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4 # Be sure to use an up to date version of R and Matrix eQTL.
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5
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6 # source("Matrix_eQTL_R/Matrix_eQTL_engine.r");
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7 library(MatrixEQTL)
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8
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9 ## Location of the package with the data files.
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10 base.dir = find.package('MatrixEQTL');
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11 # base.dir = '.';
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12
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13 ## Settings
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14
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15 # Linear model to use, modelANOVA, modelLINEAR, or modelLINEAR_CROSS
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16 useModel = modelLINEAR; # modelANOVA, modelLINEAR, or modelLINEAR_CROSS
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17
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18 # Genotype file name
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19 SNP_file_name = paste(base.dir, "/data/SNP.txt", sep="");
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20 snps_location_file_name = paste(base.dir, "/data/snpsloc.txt", sep="");
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21
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22 # Gene expression file name
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23 expression_file_name = paste(base.dir, "/data/GE.txt", sep="");
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24 gene_location_file_name = paste(base.dir, "/data/geneloc.txt", sep="");
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25
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26 # Covariates file name
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27 # Set to character() for no covariates
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28 covariates_file_name = paste(base.dir, "/data/Covariates.txt", sep="");
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29
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30 # Output file name
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31 output_file_name_cis = tempfile();
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32 output_file_name_tra = tempfile();
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33
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34 # Only associations significant at this level will be saved
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35 pvOutputThreshold_cis = 2e-2;
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36 pvOutputThreshold_tra = 1e-2;
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37
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38 # Error covariance matrix
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39 # Set to numeric() for identity.
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40 errorCovariance = numeric();
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41 # errorCovariance = read.table("Sample_Data/errorCovariance.txt");
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42
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43 # Distance for local gene-SNP pairs
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44 cisDist = 1e6;
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45
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46 ## Load genotype data
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47
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48 snps = SlicedData$new();
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49 snps$fileDelimiter = "\t"; # the TAB character
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50 snps$fileOmitCharacters = "NA"; # denote missing values;
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51 snps$fileSkipRows = 1; # one row of column labels
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52 snps$fileSkipColumns = 1; # one column of row labels
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53 snps$fileSliceSize = 2000; # read file in slices of 2,000 rows
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54 snps$LoadFile(SNP_file_name);
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55
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56 ## Load gene expression data
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57
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58 gene = SlicedData$new();
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59 gene$fileDelimiter = "\t"; # the TAB character
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60 gene$fileOmitCharacters = "NA"; # denote missing values;
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61 gene$fileSkipRows = 1; # one row of column labels
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62 gene$fileSkipColumns = 1; # one column of row labels
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63 gene$fileSliceSize = 2000; # read file in slices of 2,000 rows
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64 gene$LoadFile(expression_file_name);
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65
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66 ## Load covariates
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67
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68 cvrt = SlicedData$new();
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69 cvrt$fileDelimiter = "\t"; # the TAB character
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70 cvrt$fileOmitCharacters = "NA"; # denote missing values;
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71 cvrt$fileSkipRows = 1; # one row of column labels
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72 cvrt$fileSkipColumns = 1; # one column of row labels
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73 if(length(covariates_file_name)>0) {
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74 cvrt$LoadFile(covariates_file_name);
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75 }
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76
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77 ## Run the analysis
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78 snpspos = read.table(snps_location_file_name, header = TRUE, stringsAsFactors = FALSE);
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79 genepos = read.table(gene_location_file_name, header = TRUE, stringsAsFactors = FALSE);
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80
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81 me = Matrix_eQTL_main(
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82 snps = snps,
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83 gene = gene,
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84 cvrt = cvrt,
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85 output_file_name = output_file_name_tra,
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86 pvOutputThreshold = pvOutputThreshold_tra,
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87 useModel = useModel,
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88 errorCovariance = errorCovariance,
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89 verbose = TRUE,
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90 output_file_name.cis = output_file_name_cis,
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91 pvOutputThreshold.cis = pvOutputThreshold_cis,
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92 snpspos = snpspos,
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93 genepos = genepos,
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94 cisDist = cisDist,
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95 pvalue.hist = TRUE,
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96 min.pv.by.genesnp = TRUE,
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97 noFDRsaveMemory = FALSE);
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98
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99 unlink(output_file_name_tra);
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100 unlink(output_file_name_cis);
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101
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102 ## Results:
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103
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104 cat('Analysis done in: ', me$time.in.sec, ' seconds', '\n');
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105 cat('Detected local eQTLs:', '\n');
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106 show(me$cis$eqtls)
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107 cat('Detected distant eQTLs:', '\n');
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108 show(me$trans$eqtls)
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109
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110 ## Plot the histogram of local and distant p-values
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111
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112 plot(me)
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