Output files
', "\n") - cat( '
- ', "\n" )
- cat( '
- ', htmlLink( path=robjReadCoName, robjReadCoName ), ' ', "\n" ) - cat( '
- QDNAseq object with read counts per bin, ', readCoSize,' ', "\n" ) - + cat( '
- ', htmlLink( path=robjCopyNrName, robjCopyNrName ), ' ', "\n" ) - cat( '
- QDNAseq object with copy numbers per bin, ', copyNrSize,' ', "\n" ) - - cat( '
- ', htmlLink( path=igvCopyNrName, igvCopyNrName ), ' ', "\n" ) - cat( '
- IGV formatted text file with copy numbers per bin, ', igvCopyNrSize,' ', "\n" ) - - if ( doCall ){ - cat( '
- ', htmlLink( path=robjCalledName, robjCalledName ), ' ', "\n" ) - cat( '
- QDNAseq object with segment and call status per bin, ', calledSize,' ', "\n" ) - - cat( '
- ', htmlLink( path=regiOutputName, regiOutputName ), ' ', "\n" ) - cat( '
- list with segmented/called regions for each sample, ', regionSize, ' ', "\n" ) - } - cat( '', "\n" ) - - r_code <- '## start own downstream analysis in R with:' - r_code <- c( r_code, 'library( QDNAseq )' ) - r_code <- c( r_code, paste( 'readRDS( ', robjReadCoName, ' ) -> readCounts', sep="") ) - - ## r_code shows example code on how to load output files - #cat( r_code, "\n", sep="\n") - cat( '
This table contains output files that can be used for local downstream analysis with the bioconductor QDNAseq package. For each bin-size / data-level there is a R data structure file with data of all samples. See ', htmlLink( WEB_LINK, 'the bioconductor QDNAseq documentation' ), ' for more information on how to work with these files
', "\n", sep='') + cat( '| Type | ', as.vector( mapply( paste, "", binSizes, "kbp | ", sep="" ) ),'', "\n" ) + cat( "", "\n") + files <- list() + fileTypes <- c( 'ReadCounts.rds', 'CopyNumbers.rds' ) + if ( doSegment ){ fileTypes <- c( fileTypes, 'CopyNumbersSegmented.rds') } - cat( '
|---|
Results: overview
', "\n") + cat( '
This table contains the visual results of the copy number aberration analysis. You can click on an image to jump to the larger version. If segmentation was performed as well the number of segments is shown and a file with genomic regions can be downloaded (just remember to inspect the results carefully as this is a more exprimental step).
', "\n", sep='') plots_html <- '' - - cat( '| Sample / File | CopyNr | Calls | Reads | Regions | Files | Image | " + if ( doSegment ){ # extra column with segment info + colspan <- 2 + binHeader <- "Image | Segments | " + } + cat( '
|---|
| ', as.vector( mapply( paste, " | ", binSizes, "kbp | ", sep="" ) ), '||
|---|---|---|---|
| Sample / File | Reads | ', rep( binHeader, length(binSizes) ), '||
| ', bam_file, ' | ', usedReads, ' | ', sep='' ) - html_copy_thumb <- htmlLink( path=paste('#', copy_img, sep=''), paste('', html_copy_thumb, ' | ' ) - if ( doCall ){ - call_img <- plotted_images[[ bam_file ]][[ 'Called' ]] - region_count <- plotted_images[[ bam_file ]][[ 'region_count' ]] - html_call_thumb <- htmlLink( path=paste('#', call_img, sep=''), paste('', region_count, ' (', html_bedGraph, ') | ', sep="" ) + } + plots_html <- paste( plots_html, html_copy_img, "\n", html_segm_img, "\n
Results: Analysis plots
', "\n") - cat( extra_plots_html, "\n") cat( '
Results: Sample plots
', "\n") + ## now include (large) images in html page cat( plots_html, "\n") cat( "\n
\n") cat( "\n\n") @@ -536,8 +509,6 @@ cat( 'Explore the results directly within galaxy
', "\n", sep="") cat( 'Or download a zipfile with all output (', zippedSize, ')
', "\n", sep="" ) - cat( 'The zip file contains all output files, including *.rds files allowing you to load the R copyNumber object(s) and perform further detailed analysis or create your own output for further processing. You can load the rds file with loadRDS(file.rds)