Mercurial > repos > bgruening > deeptools_compute_gc_bias
changeset 6:a66bf1fdd4b4 draft
planemo upload for repository https://github.com/fidelram/deepTools/tree/master/galaxy/wrapper/ commit 54a10cf268ca9a5399f13458a1b218be7891bd41
| author | bgruening |
|---|---|
| date | Wed, 23 Dec 2015 03:55:49 -0500 |
| parents | 511d00417d91 |
| children | f1b7a3555d34 |
| 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 tool_dependencies.xml |
| diffstat | 9 files changed, 16 insertions(+), 11 deletions(-) [+] |
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--- a/computeGCBias.xml Tue Dec 22 13:43:03 2015 -0500 +++ b/computeGCBias.xml Wed Dec 23 03:55:49 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:: $PATH_TO_IMAGES/QC_GCplots_input.png -You can find more details on the computeGCBias doc page: https://deeptools.readthedocs.org/en/release-1.6/content/tools/computeGCBias.html +You can find more details on the computeGCBias wiki page: computeGCBias wiki: https://github.com/fidelram/deepTools/wiki/QC#wiki-computeGCbias **Output files**:
--- a/deepTools_macros.xml Tue Dec 22 13:43:03 2015 -0500 +++ b/deepTools_macros.xml Wed Dec 23 03:55:49 2015 -0500 @@ -40,10 +40,10 @@ </xml> <token name="@HEATMAP_OPTIONS@"> - #if str($plotting_type.zMin) != "": + #if $plotting_type.zMin: --zMin $plotting_type.zMin #end if - #if str($plotting_type.zMax) != "": + #if $plotting_type.zMax: --zMax $plotting_type.zMax #end if --colorMap '$plotting_type.colorMap' @@ -107,11 +107,7 @@ </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: 0 [do not cluster])."/> + 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)."/> </when> <when value="none" /> </conditional> @@ -412,6 +408,7 @@ <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> @@ -459,6 +456,14 @@ </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> ((
--- a/test-data/bamCoverage_result3.bg Tue Dec 22 13:43:03 2015 -0500 +++ b/test-data/bamCoverage_result3.bg Wed Dec 23 03:55:49 2015 -0500 @@ -5,4 +5,4 @@ chrM 220 230 7690304.31 chrM 230 240 6027535.81 chrM 240 250 3325537.00 -chrM 250 16569 623538.2 +chrM 250 260 623538.19
--- a/tool_dependencies.xml Tue Dec 22 13:43:03 2015 -0500 +++ b/tool_dependencies.xml Wed Dec 23 03:55:49 2015 -0500 @@ -4,6 +4,6 @@ <repository changeset_revision="a28e3c30828d" name="package_python_2_7_10" owner="iuc" toolshed="https://testtoolshed.g2.bx.psu.edu" /> </package> <package name="deepTools" version="2.0"> - <repository changeset_revision="747571992679" name="package_python_2_7_deeptools_2_0" owner="iuc" toolshed="https://testtoolshed.g2.bx.psu.edu" /> + <repository changeset_revision="bd40c0aa7d8e" name="package_python_2_7_deeptools_2_0" owner="iuc" toolshed="https://testtoolshed.g2.bx.psu.edu" /> </package> </tool_dependency>