Mercurial > repos > bgruening > deeptools_compute_gc_bias
changeset 7:f1b7a3555d34 draft
planemo upload for repository https://github.com/fidelram/deepTools/tree/master/galaxy/wrapper/ commit ae00542731230245927953207977833a0f020b69
| author | bgruening |
|---|---|
| date | Wed, 23 Dec 2015 07:30:00 -0500 |
| parents | a66bf1fdd4b4 |
| children | 3d2d0cf4fd17 |
| files | computeGCBias.xml deepTools_macros.xml static/images/plotCorrelation_galaxy_bw_heatmap_output.png test-data/bamCoverage_result1.bw test-data/bamCoverage_result2.bw test-data/bamCoverage_result3.bg test-data/plotPCA_result1.png test-data/profiler_result2.png |
| diffstat | 8 files changed, 10 insertions(+), 15 deletions(-) [+] |
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--- a/computeGCBias.xml Wed Dec 23 03:55:49 2015 -0500 +++ b/computeGCBias.xml Wed Dec 23 07:30:00 2015 -0500 @@ -141,7 +141,7 @@ In order to estimate how many reads with what kind of GC content one should have sequenced, we first need to determine how many regions the specific reference genome contains for each amount of GC content, i.e. how many regions in the genome have 50% GC (or 10% GC or 90% GC or...). -We then sample a large number of equally sized genome bins and count how many times we see a bin with 50% GC (or 10% GC or 90% or...). These EXPECTED values are independent of any +We then sample a large number of equally sized genome bins and count how many times we see a bin with 50% GC (or 10% GC or 90% or...). These EXPECTED values are independent of any sequencing as it only depends on the respective reference genome (i.e. it will most likely vary between mouse and fruit fly due to their genome's different GC contents). The OBSERVED values are based on the reads from the sequenced sample. Instead of noting how many genomic regions there are per GC content, we now count the reads per GC content. In an ideal sample without GC bias, the ratio of OBSERVED/EXPECTED values should be close to 1 regardless of the GC content. Due to PCR (over)amplifications, the majority of ChIP samples @@ -150,7 +150,7 @@ .. image:: $PATH_TO_IMAGES/QC_GCplots_input.png -You can find more details on the computeGCBias wiki page: computeGCBias wiki: https://github.com/fidelram/deepTools/wiki/QC#wiki-computeGCbias +You can find more details on the computeGCBias doc page: https://deeptools.readthedocs.org/en/release-1.6/content/tools/computeGCBias.html **Output files**:
--- a/deepTools_macros.xml Wed Dec 23 03:55:49 2015 -0500 +++ b/deepTools_macros.xml Wed Dec 23 07:30:00 2015 -0500 @@ -40,10 +40,10 @@ </xml> <token name="@HEATMAP_OPTIONS@"> - #if $plotting_type.zMin: + #if str($plotting_type.zMin) != "": --zMin $plotting_type.zMin #end if - #if $plotting_type.zMax: + #if str($plotting_type.zMax) != "": --zMax $plotting_type.zMax #end if --colorMap '$plotting_type.colorMap' @@ -107,7 +107,11 @@ </param> <when value="kmeans"> <param name="k_kmeans" type="integer" value="0" label="Number of clusters to compute" - help="When this option is set, then the matrix is split into clusters using the kmeans algorithm. Only works for data that is not grouped, otherwise only the first group will be clustered. If more specific clustering methods are required it is advisable to save the underlying matrix and run the clustering using other software. The plotting of the clustering may fail (Error: Segmentation fault) if a cluster has very few members compared to the total number or regions. (default: None)."/> + help="When this option is set, then the matrix is split into clusters using the kmeans algorithm. + Only works for data that is not grouped, otherwise only the first group will be clustered. + If more specific clustering methods are required it is advisable to save the underlying matrix and + run the clustering using other software. The plotting of the clustering may fail (Error: Segmentation fault) + if a cluster has very few members compared to the total number or regions. (default: 0 [do not cluster])."/> </when> <when value="none" /> </conditional> @@ -408,7 +412,6 @@ <when value="no" /> <when value="yes"> <yield /> - <param name="saveData" type="boolean" label="Save the data underlying the average profile"/> <param name="saveSortedRegions" type="boolean" label="Save the regions after skipping zeros or min/max threshold values" help="The order of the regions in the file follows the sorting order selected. This is useful, for example, to generate other heatmaps keeping the sorting of the first heatmap."/> </when> </conditional> @@ -456,14 +459,6 @@ </xml> <xml name="output_graphic_outputs"> - <data format="tabular" name="outFileNameData" label="${tool.name} on ${on_string}: averages per matrix column"> - <filter> - (( - output['showOutputSettings'] == 'yes' and - output['saveData'] is True - )) - </filter> - </data> <data format="bed" name="outFileSortedRegions" label="${tool.name} on ${on_string}: sorted/filtered regions"> <filter> ((