comparison edgeR_Differential_Gene_Expression.xml @ 115:f06dceb5b966 draft

planemo upload for repository https://bitbucket.org/EMCbioinf/galaxy-tool-shed-tools/raw/master/edger_with_design_matrix commit 097f2974042345a231e431299a031f236f3eb689-dirty

114:5d7efbca6c75

<?xml version="1.0" encoding="UTF-8"?>
<tool id="edger_dge" name="edgeR: Differential Gene(Expression) Analysis" version="3.11.0.a">
    <description>RNA-Seq gene expression analysis using edgeR (R package)</description>
    
    <macros>
        <import>edgeR_macros.xml</import>
    </macros>

                /dev/null
            #end if
            
            $output_format_images
            '
            #if $output_R:
                > $output_R
            #end if
    </command>
    
    <configfiles>
        <configfile name="R_script">
<![CDATA[

      }
      
      diff_x <- abs(max(mds_distance_logFC\$x)-min(mds_distance_logFC\$x))
      diff_y <-(max(mds_distance_logFC\$y)-min(mds_distance_logFC\$y))
      plot(c(min(mds_distance_logFC\$x),max(mds_distance_logFC\$x) + 0.45 * diff_x), c(min(mds_distance_logFC\$y) - 0.05 * diff_y,max(mds_distance_logFC\$y) + 0.05 * diff_y), main="edgeR logFC-MDS Plot on top 500 genes",type="n", xlab="Leading logFC dim 1", ylab="Leading logFC dim 2")
      mds_distance_logFC(mds_distance_logFC\$x,mds_distance_logFC\$y,pch=20)
      text(mds_distance_logFC\$x, mds_distance_logFC\$y,rownames(dge\$samples),cex=1.25,col="gray",pos=4)
      rm(diff_x,diff_y)
      
      dev.off()
      }

    }
    
    diff_x <- abs(max(mds_distance_BCV\$x)-min(mds_distance_BCV\$x))
    diff_y <- (max(mds_distance_BCV\$y)-min(mds_distance_BCV\$y))
    plot(c(min(mds_distance_BCV\$x),max(mds_distance_BCV\$x) + 0.45 * diff_x), c(min(mds_distance_BCV\$y) - 0.05 * diff_y,max(mds_distance_BCV\$y) + 0.05 * diff_y), main="edgeR BCV-MDS Plot",type="n", xlab="Leading BCV dim 1", ylab="Leading BCV dim 2")
    mds_distance_BCV(mds_distance_BCV\$x,mds_distance_BCV\$y,pch=20)
    text(mds_distance_BCV\$x, mds_distance_BCV\$y,rownames(dge\$samples),cex=1.25,col="gray",pos=4)
    rm(diff_x,diff_y)
    
    dev.off()
  }

            <option value="make_output_BCVplot">BCV-plot</option>
            <option value="make_output_MAplot">MA-plot</option>
            <option value="make_output_PValue_distribution_plot">P-Value distribution plot</option>
            <option value="make_output_hierarchical_clustering_plot">Hierarchical custering</option>
            <option value="make_output_heatmap_plot">Heatmap</option>
            
            <option value="make_output_R_stdout">R stdout</option>
            <option value="make_output_RData_obj">R Data object</option>
        </param>
        
        <param name="output_format_images" type="select" label="Output format of images" display="radio">
            <option value="png">Portable network graphics (.png)</option>

115:f06dceb5b966

<?xml version="1.0" encoding="UTF-8"?>
<tool id="edger_dge" name="edgeR: Differential Gene(Expression) Analysis" version="3.11.0.b">
    <description>RNA-Seq gene expression analysis using edgeR (R package)</description>
    
    <macros>
        <import>edgeR_macros.xml</import>
    </macros>

                /dev/null
            #end if
            
            $output_format_images
            '
    </command>
    
    <configfiles>
        <configfile name="R_script">
<![CDATA[

      }
      
      diff_x <- abs(max(mds_distance_logFC\$x)-min(mds_distance_logFC\$x))
      diff_y <-(max(mds_distance_logFC\$y)-min(mds_distance_logFC\$y))
      plot(c(min(mds_distance_logFC\$x),max(mds_distance_logFC\$x) + 0.45 * diff_x), c(min(mds_distance_logFC\$y) - 0.05 * diff_y,max(mds_distance_logFC\$y) + 0.05 * diff_y), main="edgeR logFC-MDS Plot on top 500 genes",type="n", xlab="Leading logFC dim 1", ylab="Leading logFC dim 2")
      points(mds_distance_logFC\$x,mds_distance_logFC\$y,pch=20)
      text(mds_distance_logFC\$x, mds_distance_logFC\$y,rownames(dge\$samples),cex=1.25,col="gray",pos=4)
      rm(diff_x,diff_y)
      
      dev.off()
      }

    }
    
    diff_x <- abs(max(mds_distance_BCV\$x)-min(mds_distance_BCV\$x))
    diff_y <- (max(mds_distance_BCV\$y)-min(mds_distance_BCV\$y))
    plot(c(min(mds_distance_BCV\$x),max(mds_distance_BCV\$x) + 0.45 * diff_x), c(min(mds_distance_BCV\$y) - 0.05 * diff_y,max(mds_distance_BCV\$y) + 0.05 * diff_y), main="edgeR BCV-MDS Plot",type="n", xlab="Leading BCV dim 1", ylab="Leading BCV dim 2")
    points(mds_distance_BCV\$x,mds_distance_BCV\$y,pch=20)
    text(mds_distance_BCV\$x, mds_distance_BCV\$y,rownames(dge\$samples),cex=1.25,col="gray",pos=4)
    rm(diff_x,diff_y)
    
    dev.off()
  }

            <option value="make_output_BCVplot">BCV-plot</option>
            <option value="make_output_MAplot">MA-plot</option>
            <option value="make_output_PValue_distribution_plot">P-Value distribution plot</option>
            <option value="make_output_hierarchical_clustering_plot">Hierarchical custering</option>
            <option value="make_output_heatmap_plot">Heatmap</option>
            <option value="make_output_RData_obj">R Data object</option>
        </param>
        
        <param name="output_format_images" type="select" label="Output format of images" display="radio">
            <option value="png">Portable network graphics (.png)</option>