Mercurial > repos > kpbioteam > ewastools
changeset 77:c7e8fdb9f1db draft
Deleted selected files, upload complex tool
| author | kpbioteam |
|---|---|
| date | Sun, 26 Jan 2020 16:51:33 -0500 |
| parents | fef50103f6b3 |
| children | e67f424d3f42 |
| files | minfi_dmp.xml minfi_dmr.xml minfi_dropsnp.xml minfi_getbeta.xml minfi_getcn.xml minfi_getm.xml minfi_getsnp.xml minfi_maptogenome.xml minfi_mset.xml minfi_ppfun.xml minfi_ppquantile.xml minfi_qc.xml minfi_read450k.xml minfi_rset.xml |
| diffstat | 14 files changed, 0 insertions(+), 707 deletions(-) [+] |
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--- a/minfi_dmp.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,88 +0,0 @@ -<tool id="minfi_dmp" name="Minfi DMP" version="@MINFI_VERSION@"> - <description>to find differentially methylated positions</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"><![CDATA[ - Rscript '$minfi_dmp_script' - ]]></command> - <configfiles> - <configfile name="minfi_dmp_script"><![CDATA[ -require("minfi", quietly = TRUE) - -set <- get(load('$grset')) - -genomeranges <- as.data.frame(ranges(set)) - -beta <- getBeta(set) - -pheno <- read.table('$phenotype_table',skip=1) - -type <- '$phenotype' - -qCutoff <- as.numeric('$q_cutoff') - -shrinkVar <- '$variance_shrinkage' - -tab <- read.table('$ucsc_genome') - -tab <- tab[,-(11:14),drop=FALSE] - -tab <- tab[,c(1,4,5,10)] - -colnames(tab) <- c('chr','start','end','names') - -dmp <- dmpFinder(beta, pheno[,"V2"], type = type, qCutoff = qCutoff, shrinkVar = shrinkVar) - -dmp[,"names"] <- rownames(dmp) - -data <- merge(dmp, tab, by="names",sort = TRUE) - -data <- data[,c(6,7,8,1,4,5)] - -write.table(data, file= '$dmp', quote = FALSE,col.names = TRUE, row.names = FALSE, sep = "\t") -]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="grset" format="rdata" label="Data Mapped To The Genome" help="MethylSet, RatioSet or GenomicRatioSet" /> - <param type="data" name="phenotype_table" format="tabular" label="Phenotype Table"/> - <param name="phenotype" type="select" label="Phenotype Type"> - <option value="categorical">categorical</option> - <option value="continuous">continuous</option> - </param> - <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."/> - <param name="variance_shrinkage" type="boolean" truevalue="TRUE" falsevalue="FALSE" label="Variance Shrinkage" - help="Enable variance shrinkage is recommended when sample sizes are small"/> - <param type="data" name="ucsc_genome" format="gtf" label="Genome Table" help="UCSC genome data Methyl450"/> - </inputs> - <outputs> - <data name="dmp" format="interval" label="Differentially Methylated Positions"/> - </outputs> - <tests> - <test> - <param name="grset" value="GRSet_without_SNPs.rdata"/> - <param name="phenotype_table" value="phenotypeTable.txt"/> - <param name="phenotype" value="categorical"/> - <param name="q_cutoff" value="1"/> - <param name="variance_shrinkage" value="FALSE"/> - <param name="ucsc_genome" value="ucsc.gtf"/> - <output name="dmp" file="Differentially_Methylated_Positions.interval"/> - </test> - </tests> - <help><![CDATA[ -This tool creates differentially methylated positions (DMPs) with respect to a phenotype covariate. The phenotype may be categorical (e.g. cancer vs. normal) or continuous (e.g. blood pressure). - -The output is an interval file with the following columns: - - - chr - - start - - end - - names - - pvalue - - qval - - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_dmr.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,101 +0,0 @@ -<tool id="minfi_dmr" name="Minfi DMR" version="@MINFI_VERSION@"> - <description>to find differentially methylated regions</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_dmr_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_dmr_script"> - <![CDATA[ -require("minfi", quietly = TRUE) -options(warn = -1) - -GRSet <- get(load('$grset')) - -pheno <- read.table('$phenotype_table',skip = 1) - -group <- pheno\$V2 - -pair <- factor(pheno\$V3) - -design.matrix <- model.matrix(~ group + pair) - -maxGap <- as.numeric('$maxgap_size') - - if(is.null(GRSet\$cluster)){ - cluster = NULL - maxGap = maxGap -} else { - cluster = GRSet\$cluster - maxGap = NULL -} - -cutoff <- as.numeric('$cutoff_size') -B <- as.numeric('$number_of_resamples') -nullMethod <- '$null_method' -coef <- 2 - -dmrs <- bumphunter(GRSet, - design = design.matrix, - cluster = cluster, - maxGap = maxGap, - cutoff = cutoff, - nullMethod = nullMethod, - B = B) - -dmrGR <- dmrs\$table[,c(1,2,3)] -colnames(dmrGR) <- c("chr","start","end") - -write.table(dmrGR, file= '$dmr', quote = FALSE,col.names = TRUE, row.names = FALSE, sep = "\t") - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="grset" format="rdata" label="Data Mapped To The Genome" - help="This class (GenomicRatioSet) holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location." /> - <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"/> - <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"/> - <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."/> - <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."/> - <param name="null_method" type="select" label="null Method" help="Method used to generate null candidate regions."> - <option value="permutation" selected="True">permutation</option> - <option value="bootstrap">bootstrap</option> - </param> - </inputs> - <outputs> - <data name="dmr" format="interval" label="Differentially Methylated Regions"/> - </outputs> - <tests> - <test> - <param name="grset" value="GRSet_without_SNPs.rdata"/> - <param name="phenotype_table" value="phenotypeTable.txt"/> - <param name="maxgap_size" value="250"/> - <param name="cutoff_size" value="0.1"/> - <param name="number_of_resamples" value="0"/> - <param name="null_method" value="permutation"/> - <output name="dmr" file="Differentially_Methylated_Regions.interval"/> - </test> - </tests> - <help><![CDATA[ -Genomic Ratio Set should contain 450k arrays reads for each sample listed in Phenotype Table: sampleID phenotype paired e.g. GSM1588708 sensitive 1 - -This tool is a version of the bump hunting algorithm (Andrew E Jaffe et al. 2012) adapted to the 450k array finding find differentially methylated regions DMR. - -The output is an interval file with the following columns: - - - chr - - start - - end - - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_dropsnp.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,45 +0,0 @@ -<tool id="minfi_dropsnp" name="Minfi Drop SNPs" version="@MINFI_VERSION@"> - <description>drop the probes that contain either a SNP at the CpG interrogation or at the single nucleotide extension</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements"> -<requirement type="package" version="0.6.0">bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19</requirement> - </expand> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_snp_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_snp_script"><![CDATA[ -require("minfi", quietly = TRUE) - -GRSet <- get(load('$grset')) - -GRSet <- dropLociWithSnps(GRSet, snps=c("SBE","CpG"), maf=0) - -save(GRSet,file = '$grsetwithoutsnp') - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="grset" format="rdata" label="Genomic Ratio Set" - help="This class holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location."/> - </inputs> - <outputs> - <data name="grsetwithoutsnp" format="rdata" from_work_dir="dropsnpGRSet.rdata" label="Data Mapped To The Genome without SNPs"/> - </outputs> - <tests> - <test> - <param name="grset" value="GRSet.rdata"/> - <output name="grsetwithoutsnp" file="GRSet_without_SNPs.rdata"/> - </test> - </tests> - <help><![CDATA[ -This tool is a version of the dropLociWithSnps function adapted to drop the probes that contain either a SNP at the CpG interrogation or at the single nucleotide extension (recommend). - -The output is a GenomicRatioSet object without SNPs loci. - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_getbeta.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,41 +0,0 @@ -<tool id="minfi_getbeta" name="Minfi Get Beta" version="@MINFI_VERSION@"> - <description>obtain Beta value matrix</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_beta_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_beta_script"><![CDATA[ -require("minfi", quietly = TRUE) - -MSet <- get(load('$mset')) - -beta <- getBeta(MSet) - -write.table(beta, file = '$matrix', quote = FALSE, sep = "\t") - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="mset" format="rdata" label="MethylSet" - help="This class holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location."/> - </inputs> - <outputs> - <data name="matrix" format="bedgraph" label="Beta Values Matrix"/> - </outputs> - <tests> - <test> - <param name="mset" value="MethylSet.rdata"/> - <output name="matrix" file="Beta_Values_Matrix.bedgraph"/> - </test> - </tests> - <help><![CDATA[ - This tools outputs an interval file of methylation indices (beta values), which are continuous values between 0 and 1 representing the ratio/fraction of the intensity of the methylated-probe signal to the total signal intensity for each probed CpG site. - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_getcn.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,40 +0,0 @@ -<tool id="minfi_getcn" name="Minfi Get CN" version="@MINFI_VERSION@"> - <description>get the coordinating node associated with this D1Client object</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_mset_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_mset_script"><![CDATA[ -require("minfi", quietly = TRUE) -MSet <- get(load('$mset')) - -CN <- getCN(MSet) - -write.table(CN, '$matrix') -]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="mset" format="rdata" label="MethylSet" - help="This class holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location."/> - </inputs> - <outputs> - <data name="matrix" format="txt" label="CN Value Matrix" /> - </outputs> - <tests> - <test> - <param name="mset" value="MethylSet.rdata"/> - <output name="matrix" file="CN_Value_Matrix.txt"/> - </test> - </tests> - <help><![CDATA[ - This tool output copy number of the values defined as the sum of the methylation and unmethylation channel for each probed CpG site. - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_getm.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,41 +0,0 @@ -<tool id="minfi_getM" name="Minfi Get M" version="@MINFI_VERSION@"> - <description>returns the Fisher information corresponding to a model and a design</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_m_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_m_script"><![CDATA[ -require("minfi", quietly = TRUE) -MSet <- get(load('$mset')) - -m <- getM(MSet) - -write.table(m, '$matrix') - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="mset" format="rdata" label="MethylSet" - help="This class holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location."/> - </inputs> - <outputs> - <data name="matrix" format="txt" label="M Value Matrix"/> - </outputs> - <tests> - <test> - <param name="mset" value="MethylSet.rdata"/> - <output name="matrix" file="M_Value_Matrix.txt"/> - </test> - </tests> - <help><![CDATA[ - This tool output M value the logit representation of methylation level ratio based on intensities between methylated and unmethylated alleles in each probed CpG site. - ]]></help> - <expand macro="citations" /> -</tool> -
--- a/minfi_getsnp.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,44 +0,0 @@ -<tool id="minfi_getsnp" name="Minfi Get SNPs" version="@MINFI_VERSION@"> - <description>retrieve the chromosome and the position of each SNP</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements"> - <requirement type="package" version="0.6.0">bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19</requirement> - </expand> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_snp_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_snp_script"><![CDATA[ -require("minfi", quietly = TRUE) - -GRSet <- get(load('$grset')) - -snps <- getSnpInfo(GRSet) - -write.table(snps, '$table') - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="grset" format="rdata" label="Data Mapped To The Genome" - help="This class (GenomicRatioSet) holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location."/> - </inputs> - <outputs> - <data name="table" format="txt" label="SNPInfo Table"/> - </outputs> - <tests> - <test> - <param name="grset" value="GRSet.rdata"/> - <output name="table" file="SNPInfo_Table.txt"/> - </test> - </tests> - <help><![CDATA[ - This tool is a version of the getSnpInfo adapted to retrieve the chromosome and the position of each SNP on a given Affymetrix SNP Array. - ]]></help> - <expand macro="citations" /> -</tool> -
--- a/minfi_maptogenome.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,43 +0,0 @@ -<tool id="minfi_maptogenome" name="Minfi Map to Genome" version="@MINFI_VERSION@"> - <description>mapping Ilumina methylation array data to the genome</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements"> - <requirement type="package" version="0.6.0">bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19</requirement> - </expand> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_mtg_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_mtg_script"><![CDATA[ -require("minfi", quietly = TRUE) -require("IlluminaHumanMethylation450kanno.ilmn12.hg19", quietly = TRUE) - -RSet <- get(load('$rset')) - -GRSet <- mapToGenome(RSet) - -save(GRSet,file = '$grset') - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="rset" format="rdata" label="Methylation Data to Map" help="This class holds preprocessed data for Illumina methylation microarrays." /> - </inputs> - <outputs> - <data name="grset" format="rdata" from_work_dir="GRSet.rdata" label= "Data Mapped To The Genome" /> - </outputs> - <tests> - <test> - <param name="rset" value="RatioSet.rdata"/> - <output name="grset" file="GRSet.rdata"/> - </test> - </tests> - <help><![CDATA[ - This tool is mapping Ilumina methylation array data to the genome using 450k annotation package. Depending on the genome, not all methylation loci may have a genomic position. The output is an a GenomicRatioSet object. - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_mset.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,42 +0,0 @@ -<tool id="minfi_mset" name="Minfi Mset" version="@MINFI_VERSION@"> - <description>Create objects contains CpGs signals</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_mset_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_mset_script"><![CDATA[ -require("minfi", quietly = TRUE) - -RGSet <- get(load('$RGChannelSet')) - -MSet <- preprocessRaw(RGSet) - -save(MSet,file = '$MethylSet') - - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="RGChannelSet" format="rdata" label="RGChannelSet" - help="These classes represents raw (unprocessed) data from a two color micro array; specifically an Illumina methylation array."/> - </inputs> - <outputs> - <data name="MethylSet" format="rdata" label="MethylSet" /> - </outputs> - <tests> - <test> - <param name="RGChannelSet" value="RGChannelSet.rdata"/> - <output name="MethylSet" file="MethylSet.rdata"/> - </test> - </tests> - <help><![CDATA[ - This tool is transforming a class representing raw (unprocessed) data from a two color micro array - RGChannelSet into a class holding preprocessed data for Illumina methylation microarrays, mapped to genomic location - MethylSet. - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_ppfun.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,41 +0,0 @@ -<tool id="minfi_ppfun" name="Minfi Preprocess Funnorm" version="@MINFI_VERSION@"> - <description>implements the functional normalization algorithm</description><macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements"> - <requirement type="package" version="0.6.0">bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19</requirement> - </expand> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_pp_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_pp_script"><![CDATA[ -require("minfi", quietly = TRUE) -RGSet <- get(load('$rgset')) - -GRSet <- preprocessFunnorm(RGSet) - -save(GRSet,file = '$grset') - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="rgset" format="rdata" label="RGChannelSet" - help="These classes represents raw (unprocessed) data from a two color micro array; specifically an Illumina methylation array." /> - </inputs> - <outputs> - <data name="grset" format="rdata" label="GenomicRatioSet"/> - </outputs> - <tests> - <test> - <param name="rgset" value="RGChannelSet.rdata"/> - <output name="grset" file="FunGenomicRatioSet.rdata"/> - </test> - </tests> - <help><![CDATA[ - This tool uses the internal control probes present on the array to infer between-array technical variation. It is particularly useful for studies comparing conditions with known large-scale differences, such as cancer/normal studies, or between-tissue studies. It has been shown that for such studies, functional normalization outperforms other existing approaches (Jean-Philippe Fortin et al. 2014). - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_ppquantile.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,47 +0,0 @@ -<tool id="minfi_ppquantile" name="Minfi Preprocess Quantile" version="@MINFI_VERSION@"> - <description>implements stratified quantile normalization preprocessing</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements"> - <requirement type="package" version="0.6.0">bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19</requirement> - </expand> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$minfi_pp_script' - ]]> - </command> - <configfiles> - <configfile name="minfi_pp_script"><![CDATA[ -require("minfi", quietly = TRUE) -RGSet <- get(load('$rgset')) - -GRSet <- preprocessQuantile(RGSet, fixOutliers = TRUE, - removeBadSamples = TRUE, badSampleCutoff = 10.5, - quantileNormalize = TRUE, stratified = TRUE, - mergeManifest = FALSE, sex = NULL) - -save(GRSet,file = '$grset') - -]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="rgset" format="rdata" label="RGChannelSet" - help="These classes represents raw (unprocessed) data from a two color micro array; specifically an Illumina methylation array." /> - </inputs> - <outputs> - <data name="grset" format="rdata" label="GenomicRatioSet"/> - </outputs> - <tests> - <test> - <param name="rgset" value="RGChannelSet.rdata"/> - <output name="grset" file="QuantileGenomicRatioSet.rdata"/> - </test> - </tests> - <help><![CDATA[ - The normalization procedure is applied to the Meth and Unmeth intensities separately. The distribution of type I and type II signals is forced to be the same by first quantile normalizing the type II probes across samples and then interpolating a reference distribution to which we normalize the type I probes. Since probe types and probe regions are confounded and we know that DNAm distributions vary across regions we stratify the probes by region before applying this interpolation. - ]]></help> - <expand macro="citations" /> -</tool> -
--- a/minfi_qc.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,48 +0,0 @@ -<tool id="minfi_qc" name="Minfi QC" version="@MINFI_VERSION@"> - <description>provides a simple quality control matrix and plot</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$read_qc_script' - ]]> - </command> - <configfiles> - <configfile name="read_qc_script"> - <![CDATA[ -require("minfi", quietly = TRUE) - -MSet <- get(load('$MethylSet')) - -qc <- getQC(MSet) - -write.table(qc, '$qctab') - -png('$qcpng') -plotQC(qc) -dev.off() - ]]> - </configfile> - </configfiles> - <inputs> - <param type="data" name="MethylSet" format="rdata" label="MethylSet" - help="This class holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location."/> - </inputs> - <outputs> - <data name="qctab" format="txt" label="Quality Control Report"/> - <data name="qcpng" format="png" label="Quality Control Plot"/> - </outputs> - <tests> - <test> - <param name="MethylSet" value="MethylSet.rdata"/> - <output name="qctab" file="Quality_Control_Report.txt"/> - <output name="qcpng" file="Quality_Control_Plot.png" compare="sim_size"/> - </test> - </tests> - <help><![CDATA[ -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. - ]]></help> - <expand macro="citations" /> -</tool>
--- a/minfi_read450k.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,46 +0,0 @@ -<tool id="minfi_read450k" name="Minfi Read 450k" version="2.1.0"> - <description>load .IDAT files</description> - <requirements> - <requirement type="package" version="1.24.0">bioconductor-minfi</requirement> - </requirements> - <command detect_errors="exit_code"><![CDATA[ - #for $counter, $input in enumerate($files_red): - #set $redname = str( getattr( $input, 'element_identifier', 'sample' ) ).replace( "/", '-' ).replace( "\t", "-" ) - ln -s $input ./${redname} && - #end for - #for $counter, $input in enumerate($files_grn): - #set $grnname = str( getattr( $input, 'element_identifier', 'sample' ) ).replace( "/", '-' ).replace( "\t", "-" ) - ln -s $input ./${grnname} && - #end for - Rscript '$read_idat_script' - ]]></command> - <configfiles> - <configfile name="read_idat_script"><![CDATA[ - require("minfi", quietly = TRUE) - out <- read.metharray(list.files(pattern="_Red.idat")) - save(out, file = '$RGChannelSet') - ]]> </configfile> - </configfiles> - <inputs> - <param type="data" name="files_red" multiple="true" format="idat" label="Red .IDAT files"/> - <param type="data" name="files_grn" multiple="true" format="idat" label="Green .IDAT files" /> - </inputs> - <outputs> - <data name="RGChannelSet" format="rdata" label="RGChannelSet"/> - </outputs> - <tests> - <test> - <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"/> - <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"/> - <output name="RGChannelSet" file="RGChannelSet.rdata"/> - </test> - </tests> - <help><![CDATA[ -The tool loads the binary 450K array “IDAT” raw files generated by the Illumina Scanner. In addition to the methylated and an unmethylated intensity values for each 450,000 CpG positions, IDAT file contains some extra info such as control probes. - -]]></help> - <citations> - <citation type="doi">10.18129/B9.bioc.illuminaio</citation> -</citations> -</tool> -
--- a/minfi_rset.xml Fri Jun 07 08:57:26 2019 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,40 +0,0 @@ -<tool id="minfi_rset" name="Minfi Rset" version="@MINFI_VERSION@"> - <description>store Beta values and/or M values</description> - <macros> - <import>macros.xml</import> - </macros> - <expand macro="requirements" /> - <command detect_errors="exit_code"> - <![CDATA[ - Rscript '$read_rset_script' - ]]> - </command> - <configfiles> - <configfile name="read_rset_script"> -<![CDATA[ -require("minfi", quietly = TRUE) -MSet <- get(load('$mset')) - -RSet <- ratioConvert(MSet, what = "both", keepCN = TRUE) - -save(RSet,file = '$rset') - ]]> </configfile> - </configfiles> - <inputs> - <param type="data" name="mset" format="rdata" label="MethylSet" - help="This class holds preprocessed data for Illumina methylation microarrays, mapped to a genomic location."/> - </inputs> - <outputs> - <data name="rset" format="rdata" label="RatioSet"/> - </outputs> - <tests> - <test> - <param name="mset" value="MethylSet.rdata"/> - <output name="rset" file="RatioSet.rdata"/> - </test> - </tests> - <help><![CDATA[ - RSet class holds preprocessed data for Illumina methylation microarrays. It contains respectively the Beta value matrix, M value matrix and the Copy Number matrix. - ]]></help> - <expand macro="citations" /> -</tool>