Mercurial > repos > kpbioteam > ewastools
annotate minfi_analysis.xml @ 82:369fef559cfc draft default tip
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 9363395728213b6d82e606c5513709c54af4df09"
author | kpbioteam |
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date | Sun, 23 Feb 2020 17:00:42 -0500 |
parents | 8ab24a5229bd |
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"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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1 <?xml version='1.0'?> |
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2 <tool id='minfi_analysis' name='Infinium Human Methylation BeadChip' version='2.1.0'> |
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3 <description>Determines differentially methylated regions and positions from Infinium Methylation Assays</description> |
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4 <macros> |
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5 <import>macros.xml</import> |
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6 </macros> |
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7 <expand macro='requirements'> |
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8 <requirement type='package' version='0.6.0'>bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19</requirement> |
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9 </expand> |
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10 <command detect_errors='exit_code'><![CDATA[ |
78 | 11 #for $counter, $input in enumerate($files_red): |
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12 #set $redname = str( getattr( $input, 'element_identifier', 'sample' ) ).replace( '/', '-' ).replace( '\t', '-' ) |
78 | 13 ln -s $input ./${redname} && |
14 #end for | |
15 #for $counter, $input in enumerate($files_grn): | |
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16 #set $grnname = str( getattr( $input, 'element_identifier', 'sample' ) ).replace( '/', '-' ).replace( '\t', '-' ) |
78 | 17 ln -s $input ./${grnname} && |
18 #end for | |
19 Rscript '$minfi_analysis_script' | |
20 ]]></command> | |
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21 <configfiles> |
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22 <configfile name='minfi_analysis_script'><![CDATA[ |
8ab24a5229bd
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23 require('minfi', quietly = TRUE) |
8ab24a5229bd
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24 require('IlluminaHumanMethylation27kanno.ilmn12.hg19', quietly = TRUE) |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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25 require('IlluminaHumanMethylation450kanno.ilmn12.hg19', quietly = TRUE) |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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26 require('IlluminaHumanMethylationEPICanno.ilm10b4.hg19', quietly = TRUE) |
78 | 27 options(warn = -1) |
81
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28 RGSet <- read.metharray(list.files(pattern='_Red.idat')) #load .IDAT files |
78 | 29 |
30 MSet <- preprocessRaw(RGSet) #create objects contains CpGs signals | |
31 | |
32 qc <- getQC(MSet) | |
33 write.table(qc, '$qctab') #optional - provides a simple quality control matrix and plot | |
34 png('$qcpng') | |
35 plotQC(qc) | |
36 dev.off() | |
37 | |
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38 RSet <- ratioConvert(MSet, what = 'both', keepCN = TRUE) #store Beta values and/or M values |
78 | 39 GRSet <- mapToGenome(RSet) |
40 | |
41 | |
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42 if ('$optpp' == 'na' ) { |
78 | 43 GRSet <- mapToGenome(RSet) #mapping Ilumina methylation array data to the genome |
81
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44 } else if ('$optpp' == 'ppfun' ) { |
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369fef559cfc
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45 GRSet <- preprocessFunnorm(RGSet) #optional - implements the functional normalisation algorithm |
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"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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46 } else if ('$optpp' == 'ppq' ) { |
78 | 47 GRSet <- preprocessQuantile(RGSet, fixOutliers = TRUE, |
48 removeBadSamples = TRUE, badSampleCutoff = 10.5, | |
49 quantileNormalize = TRUE, stratified = TRUE, | |
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50 mergeManifest = FALSE, sex = NULL) #optional - implements stratified quantile normalisation preprocessing |
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"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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51 } else if ('$optpp' == 'ppsnp' ) { |
78 | 52 snps <- getSnpInfo(GRSet) #optional - retrieve the chromosome and the position of each SNP |
53 write.table(snps, '$table') | |
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369fef559cfc
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 9363395728213b6d82e606c5513709c54af4df09"
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54 GRSet <- dropLociWithSnps(GRSet, snps=c('SBE','CpG'), maf=0) #optional - drop the probes that contain either an SNP at the CpG interrogation or at the single nucleotide extensions |
78 | 55 } |
56 pheno <- read.table('$phenotype_table',skip = 1) | |
57 group <- pheno\$V2 | |
58 pair <- factor(pheno\$V3) | |
59 | |
60 design.matrix <- model.matrix(~ group + pair) | |
61 | |
62 maxGap <- as.numeric('$maxgap_size') | |
63 if(is.null(GRSet\$cluster)){ | |
64 cluster = NULL | |
65 maxGap = maxGap | |
66 } else { | |
67 cluster = GRSet\$cluster | |
68 maxGap = NULL | |
69 } | |
70 | |
71 dmrs <- bumphunter(GRSet, | |
72 design = design.matrix, | |
73 cluster = cluster, | |
74 maxGap = maxGap, | |
75 cutoff = as.numeric('$cutoff_size'), | |
76 nullMethod = '$null_method', | |
77 B = as.numeric('$number_of_resamples')) | |
78 dmrGR <- dmrs\$table[,c(1,2,3)] | |
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"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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79 colnames(dmrGR) <- c('chr','start','end') |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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80 write.table(dmrGR, file= '$dmr', quote = FALSE,col.names = TRUE, row.names = FALSE, sep = '\t') |
78 | 81 |
82 tab <- read.table('$ucsc_genome') | |
83 tab <- tab[,-(11:14),drop=FALSE] | |
84 tab <- tab[,c(1,4,5,10)] | |
85 colnames(tab) <- c('chr','start','end','names') | |
86 | |
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87 dmp <- dmpFinder(dat = getBeta(GRSet),pheno = read.table('$phenotype_table',skip=1)[,'V2'], type = '$phenotype', qCutoff = as.numeric('$q_cutoff'), shrinkVar = '$variance_shrinkage') |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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88 dmp[,'names'] <- rownames(dmp) |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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89 data <- merge(dmp, tab, by='names',sort = TRUE) |
78 | 90 data <- data[,c(6,7,8,1,4,5)] |
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91 write.table(data, file= '$dmp', quote = FALSE,col.names = TRUE, row.names = FALSE, sep = '\t') |
78 | 92 |
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93 ]]></configfile> |
8ab24a5229bd
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94 </configfiles> |
8ab24a5229bd
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95 <inputs> |
8ab24a5229bd
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96 <param type='data' name='files_red' multiple='true' format='idat' label='Red .IDAT files' help='Red .IDAT files extension is followed by the unmethylated signal intensity read in the red channel.'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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97 <param type='data' name='files_grn' multiple='true' format='idat' label='Green .IDAT files' help='Green .IDAT files extension is followed by the methylated signal intensity read in the green channel.'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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98 <param name='optpp' type='select' label='(Optional) Preprocessing Method' help='Mapping Ilumina methylation array data to the genome with or without additional preprocessing methods.'> |
8ab24a5229bd
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99 <option value='na'>No Selection (use default)</option> |
8ab24a5229bd
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100 <option value='ppfun'>Preprocess Funnorm</option> |
8ab24a5229bd
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101 <option value='ppq'>Preprocess Quantile</option> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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102 <option value='ppsnp'>Remove SNPs</option> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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103 </param> |
8ab24a5229bd
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104 <param type='data' name='phenotype_table' format='tabular' label='Phenotype Table' help='Phenotype Table must include the following information: sampleID, phenotype and paird or unpaired samples column.'/> |
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105 <param name='maxgap_size' type='integer' value='250' label='maxGap Size' help='If cluster is not provided this maximum location gap will be used to define cluster.'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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106 <param name='cutoff_size' type='float' value='0.1' label='Cutoff Size' help='A numeric value. Values of the estimate of the genomic profile above the cutoff or below the negative of the cutoff will be used as candidate regions. It is possible to give two separate values (upper and lower bounds). If one value is given, the lower bound is minus the value.'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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107 <param name='number_of_resamples' type='integer' value='0' label='Number of Resamples' help='An integer denoting the number of resamples to use when computing null distributions. This defaults to 0. If permutations is supplied that defines the number of permutations/bootstraps and B is ignored.'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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108 <param name='null_method' type='select' label='null Method' help='Method used to generate null candidate regions (defaults to ‘permutation’). Note that for cases with more than one covariate the permutation approach is not generally recommended. '> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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109 <option value='permutation' selected='True'>permutation</option> |
8ab24a5229bd
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110 <option value='bootstrap'>bootstrap</option> |
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111 </param> |
8ab24a5229bd
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112 <param type='data' name='phenotype_table' format='tabular' label='Phenotype Table' help='Table of compared samples and their characteristics, may be categorical (e.g. cancer vs. normal) or continuous (e.g. blood pressure).'/> |
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113 <param name='phenotype' type='select' label='Phenotype Type'> |
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114 <option value='categorical'>categorical</option> |
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115 <option value='continuous'>continuous</option> |
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116 </param> |
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117 <param name='q_cutoff' type='float' value='1' label='qCutoff Size' help='DMPs with an FDR q-value greater than this will not be returned.'/> |
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118 <param name='variance_shrinkage' type='boolean' truevalue='TRUE' falsevalue='FALSE' label='Variance Shrinkage' help='Enable variance shrinkage is recommended when sample sizes are small.'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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119 <param type='data' name='ucsc_genome' format='gtf' label='Genome Table' help='Reference Sequence e.g. wgEncodeHaibMethyl450Gm12878SitesRep1.'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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120 </inputs> |
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121 <outputs> |
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122 <data name='qctab' format='txt' label='Quality Control Report'/> |
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"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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123 <data name='qcpng' format='png' label='Quality Control Plot'/> |
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"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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124 <data name='table' format='txt' label='SNPInfo Table'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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125 <data name='dmr' format='bed' label='Differentially Methylated Regions'/> |
8ab24a5229bd
"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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126 <data name='dmp' format='bed' label='Differentially Methylated Positions'/> |
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"planemo upload for repository https://github.com/kpbioteam/ewas_galaxy commit 323de18b21453fa652ae3abb7e847704e13a65ed"
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127 </outputs> |
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128 <tests> |
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129 <test> |
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130 <param name='files_red' value='GSM1588707_8795207119_R06C02_Red.idat,GSM1588706_8795207135_R02C02_Red.idat,GSM1588705_8795207119_R05C02_Red.idat,GSM1588704_8795207135_R01C02_Red.idat' ftype='idat'/> |
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131 <param name='files_grn' value='GSM1588707_8795207119_R06C02_Grn.idat,GSM1588706_8795207135_R02C02_Grn.idat,GSM1588705_8795207119_R05C02_Grn.idat,GSM1588704_8795207135_R01C02_Grn.idat' ftype='idat'/> |
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132 <param name='optpp' value='ppsnp'/> |
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133 <param name='grset' value='GRSet_without_SNPs.rdata'/> |
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134 <param name='phenotype_table' value='phenotypeTable.txt'/> |
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135 <param name='maxgap_size' value='250'/> |
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136 <param name='cutoff_size' value='0.1'/> |
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137 <param name='number_of_resamples' value='0'/> |
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138 <param name='null_method' value='permutation'/> |
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139 <param name='grset' value='GRSet_without_SNPs.rdata'/> |
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140 <param name='phenotype' value='categorical'/> |
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141 <param name='q_cutoff' value='1'/> |
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142 <param name='variance_shrinkage' value='FALSE'/> |
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143 <param name='ucsc_genome' value='ucsc.gtf'/> |
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144 <output name='qctab' file='Quality_Control_Report.txt'/> |
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145 <output name='qcpng' file='Quality_Control_Plot.png' compare='sim_size'/> |
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146 <output name='table' file='SNPInfo_Table.txt'/> |
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147 <output name='dmr' file='Differentially_Methylated_Regions.bed'/> |
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148 <output name='dmp' file='Differentially_Methylated_Positions.bed'/> |
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149 </test> |
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150 </tests> |
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151 <help><![CDATA[ |
78 | 152 |
153 .. class:: infomark | |
154 | |
155 **What it does** | |
156 | |
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157 The workflow combines 5 main steps, starting with raw intensity data loading (.idat) and then optional preprocessing and normalisation of the data. The next quality control step performs an additional sample check to remove low-quality data, which normalisation cannot detect. The workflow gives the user the opportunity to perform any of these preparation and data cleaning steps, including the highly recommended genetic variation annotation step resulting in single nucleotide polymorphism identification and removal. Finally, the dataset generated through all of these steps can be used to hunt (find) differentially-methylated positions (DMP)and regions (DMR) with respect to a phenotype covariate. |
78 | 158 |
159 ***Inputs*** | |
160 | |
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161 *Series of .IDAT files*: matching red and green .idat file for each sample on the chip intensity data. |
78 | 162 |
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163 *(optional) Preprocessing Methods*: by this step probes can be stratified by region via quantile normalisation or by extended implementation of functional normalisation recommended for cases where global changes are expected such as in cancer-normal comparisons. In addition unwanted probes containing either an SNP at the CpG interrogation or at the single nucleotide extension can be removed (recommended). |
78 | 164 |
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165 *Phenotype Table*: table of compared samples and their characteristics, may be categorical (e.g. cancer vs. normal) or continuous (e.g. blood pressure). |
78 | 166 |
167 ========== ============== =============== | |
168 Accession Sensitivity Treatment | |
169 ---------- -------------- --------------- | |
170 GSM1588704 sensitive MAPKi | |
171 ---------- -------------- --------------- | |
172 GSM1588705 sensitive MAPKi | |
173 ---------- -------------- --------------- | |
174 GSM1588706 resistant BRAFi | |
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175 ---------- -------------- --------------- |
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176 GSM1588707 resistant BRAFi |
78 | 177 ========== ============== =============== |
178 | |
179 *Note*: phenotype covariate table must include the following information: | |
180 sampleID/Accession, phenotype and paird or unpaired samples column | |
181 | |
182 *Genome Table*: a reference genome that contains the nucleotide sequence of the chromosomes, It is representative of a specific genome build and release. | |
183 | |
184 ***Outputs*** | |
185 | |
186 *Quality Control Report and Plot*: quality control (QC) outputs plot of the log median intensity in both the methylated (M) and unmethylated (U) channels. When plotting these two medians against each other the good samples cluster together, while failed samples tend to separate and have lower median intensities. | |
187 | |
188 *(optional) SNPInfo Table*: matrix of the chromosome and the position of each SNP on a given Affymetrix SNP Array. | |
189 | |
190 *Differentially Methylated Regions*: consecutive genomic locations differentially methylated in the same direction save as multiple track lines in a single BED file. | |
191 | |
192 *Differentially Methylated Positions*: single genomic position that has a different methylated level in two different groups of samples (or conditions) save as multiple track lines in a single BED file. | |
193 ]]></help> | |
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194 <citations> |
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195 <citation type='doi'>10.18129/B9.bioc.illuminaio</citation> |
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196 </citations> |
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197 </tool> |