Mercurial > repos > elixir-it > vinyl_score_composition
changeset 0:f5f3f1c07cf1 draft default tip
Uploaded
| author | elixir-it |
|---|---|
| date | Thu, 17 Sep 2020 09:34:57 +0000 |
| parents | |
| children | |
| files | barplot.xml test-data/barplot_output.png test-data/barplott-test.tabular tool_barp_score.R |
| diffstat | 3 files changed, 1967 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/barplot.xml Thu Sep 17 09:34:57 2020 +0000 @@ -0,0 +1,49 @@ +<tool id="barplot" name="barplot" version="1"> + <description> This tools is used to produce a barplot that shows the "importance" of the different components of scoring systems derived by VINYL</description> + <requirements> + <requirement type="package" >r-base</requirement> + </requirements> + <command> <![CDATA[ + Rscript --vanilla $__tool_directory__/tool_barp_score.R + + ####INPUT + $fileR $numsys + + ###OUTPUT + $ofile + + ]]> + </command> + <inputs> + <param format="tabular,csv" name="fileR" type="data" label="optim_out" help="Tabular VINYL containing the evaluation of different scoring systems as provided by the VINYL optimizer "/> + <param name="numsys" value="10" min="1" max="30" type="integer" label="tobecompared" help="Number of top-scoring systems to be compared"/> + + </inputs> + <outputs> + <data format="png" name="ofile" label="${tool.name} on ${on_string}: png "/> + </outputs> + <stdio> + <regex match="error" + source="stderr" + level="fatal" + description="Unknown error encountered" /> + </stdio> + <tests> + <test> + <param name="fileR" value="barplott-test.tabular" ftype="tabular" /> + <param name="numsys" value="10" ftype="integer" /> + <output name="ofile" file="barplot_output.png" ftype="png" /> + </test> + </tests> + <help> +**What it does** +VINYL is a software designed to assist in variant prioritization in medium-large cohort of patients. The program computes an aggregate score, which is based on an extensive collection of publicly available annotations, in order to identify/prioritize variants that are likely to be pathogenic or have a clinical significance. In order to derive an optimal cut off score for the variants, VINYL uses a strategy based on "survival analysis", where the pathogenicity score distribution of the affected individuals is compared with a matched cohort of unaffected individuals. +To facilitate the usage of the software, VINYL is provided in the form of a public Galaxy instance, based on the Laniakea suite. To ensure the maximum level of security, VINYL uses Encrypted data volumes for the storage of the data. + + +**Important Usage Note** +This wrapper provides a helper tool for VINYL that facilitates the "visual" comparison of the importance of the different components of the optimal VINYL scoring system. Ideally this method can be used to quickly compare any number of scoring systems, although we suggest to limit the comparison to a sensible number (ideally no more than 20). The input this to this tool is the tabular file, as produced by running the VINYL "optimizer", which recapitulates all the different scoring systems that were tested by VINYL on your dataset. This file is already sorted, and the "best" scoring systems are normally found on the top of the file. However, since we empirically observe that several of the scoring systems derived by VINYL, usually attain similar levels of acccuracy/enrichment, comparing the topN scoring systems and the relative importance of different features, can provide additional information that can help you in the selection of the most appropriate system to be applied to your specific use case. A detailed discussion of the possible applications of this tool is provided in the VINYL manual along with a simple example of how to execute the tool, and derive simple observations. +</help> + <citations> + </citations> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/barplott-test.tabular Thu Sep 17 09:34:57 2020 +0000 @@ -0,0 +1,1902 @@ +disease_clinvar score_AF score_functional score_NS score_nIND scoreeQTL scoreG scoreT scoreM scoreR scoreSP scoreGW survP totP survA totA p-value ratio score +5.13 19.53 7.1 6.74 11.19 2.25 7.93 9.49 1.81 2.91 7.99 14.9 51 1252 1 3739 1.9862014807805e-29 152.00633885645 9.88918794587558 +5.13 19.53 6.97 6.74 15.08 2.25 7.93 9.95 1.81 2.91 7.99 14.9 51 1252 1 3739 1.9862014807805e-29 152.00633885645 9.88918794587558 +5.13 19.53 2.46 2.48 11.19 2.25 7.93 2.79 1.81 2.91 7.99 11.19 51 1252 1 3739 1.9862014807805e-29 152.00633885645 9.88918794587558 +5.13 18.22 8.57 12.69 11.19 6.57 10.08 4.73 1.81 2.91 7.99 14.9 51 1252 1 3739 1.9862014807805e-29 152.00633885645 9.88918794587558 +5.13 16.11 8.57 8.47 11.19 2.25 15.85 4.46 1.81 2.91 7.99 8.33 51 1252 1 3739 1.9862014807805e-29 152.00633885645 9.88918794587558 +8.34 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 1.35 59 1252 2 3739 1.05431911471657e-32 88.1993557446039 9.87302331143187 +8.23 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 14.9 59 1252 2 3739 1.05431911471657e-32 88.1993557446039 9.87302331143187 +5.13 19.53 8.57 11.31 12.7 2.25 10.08 2.79 1.81 2.91 7.99 14.9 59 1252 2 3739 1.05431911471657e-32 88.1993557446039 9.87302331143187 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.49 1.81 2.91 7.99 17.22 59 1252 2 3739 1.05431911471657e-32 88.1993557446039 9.87302331143187 +5.13 19.53 7.1 11.38 11.19 2.25 12.96 2.79 1.81 5.3 7.99 14.9 59 1252 2 3739 1.05431911471657e-32 88.1993557446039 9.87302331143187 +5.13 18.22 8.57 11.31 11.19 2.25 10.08 2.79 1.81 2.91 7.99 16.77 59 1252 2 3739 1.05431911471657e-32 88.1993557446039 9.87302331143187 +5.13 18.22 6.31 6.74 11.19 2.25 10.08 2.79 1.81 2.91 7.99 17.43 59 1252 2 3739 1.05431911471657e-32 88.1993557446039 9.87302331143187 +5.13 19.53 8.57 6.74 14.66 2.25 10.08 2.79 1.81 2.91 7.99 8.33 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 19.53 7.1 6.74 11.19 13.46 7.93 2.79 1.81 6.99 7.99 2.78 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 19.53 7.1 1.32 16.99 2.25 7.93 8.59 7.22 2.91 7.99 5.87 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 18.94 7.1 6.74 4.62 2.25 7.93 2.79 1.81 2.91 7.99 14.9 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 18.82 8.57 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 8.33 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 18.82 8.57 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 14.9 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 18.22 8.57 11.31 11.19 6.57 10.08 2.79 1.81 2.91 4.4 14.9 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 16.52 8.57 6.74 11.19 2.25 15.85 4.46 1.81 2.91 7.99 8.33 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 16.11 6.51 6.74 11.19 2.25 10.08 4.73 1.81 2.91 7.99 14.9 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 16.11 4.82 8.52 11.19 2.25 10.08 4.46 1.81 2.91 7.99 8.33 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 16.11 4.82 3.62 11.19 6.57 10.08 2.79 1.81 2.91 2.19 8.33 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +2.21 19.53 7.1 6.74 16.99 2.25 7.93 8.59 1.81 2.91 7.99 14.9 50 1252 1 3739 7.54030916010951e-29 149.019311277868 9.75613546352676 +5.13 19.53 9.8 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 5.87 49 1252 1 3739 2.86310632238838e-28 146.032169976335 9.62271795116951 +5.13 19.53 9 6.74 11.19 2.25 10.08 2.79 1.81 2.91 7.99 14.9 49 1252 1 3739 2.86310632238838e-28 146.032169976335 9.62271795116951 +5.13 19.53 9.42 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 14.9 49 1252 1 3739 2.86310632238838e-28 146.032169976335 9.62271795116951 +5.13 19.53 9.03 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 14.9 49 1252 1 3739 2.86310632238838e-28 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2.86310632238838e-28 146.032169976335 9.62271795116951 +5.13 16.11 6.51 6.74 11.19 2.25 10.08 3.38 1.81 2.91 1.69 8.33 49 1252 1 3739 2.86310632238838e-28 146.032169976335 9.62271795116951 +5.13 16.11 2.15 8.52 11.19 6.57 10.08 2.79 1.81 2.91 2.19 8.33 49 1252 1 3739 2.86310632238838e-28 146.032169976335 9.62271795116951 +9 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 9.74 57 1252 2 3739 1.4652265257927e-31 85.1755485569933 9.61423950271932 +9 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 14.9 57 1252 2 3739 1.4652265257927e-31 85.1755485569933 9.61423950271932 +7.84 19.53 4.39 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 14.9 57 1252 2 3739 1.4652265257927e-31 85.1755485569933 9.61423950271932 +5.13 19.53 7.1 3.64 13.89 2.25 7.93 2.79 4.91 2.91 7.99 5.87 57 1252 2 3739 1.4652265257927e-31 85.1755485569933 9.61423950271932 +5.13 18.82 8.57 6.74 11.19 6.57 10.08 2.79 1.81 2.91 2.19 19.76 57 1252 2 3739 1.4652265257927e-31 85.1755485569933 9.61423950271932 +5.13 19.53 7.1 6.74 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7.93 2.79 1.81 2.91 5.67 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 5.67 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 5.28 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 4.89 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 4.89 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 4.89 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 4.51 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 4.49 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 4.09 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 3.35 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 3.35 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 2.96 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 7.54 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.58 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 4.51 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 3.69 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 6.65 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 17.6 2.79 1.81 3.72 7.99 5.63 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 17.6 2.79 1.81 3.72 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 17.21 2.79 1.81 3.6 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 14.89 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 12.96 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 2.25 11.4 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 1.59 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 1.59 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 1.59 6.14 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 1.59 6.14 2.79 1.81 2.91 7.99 5.35 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 1.59 6.14 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 13.46 7.93 2.79 1.81 2.91 4.89 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 11.19 12.03 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.99 8.91 6.14 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.99 2.25 6.14 2.79 1.81 2.91 7.99 8.33 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.99 2.25 6.14 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.53 2.25 10.08 2.79 1.81 2.91 4.43 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.53 2.25 10.08 2.79 1.81 2.91 4.43 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.53 2.25 10.08 2.79 1.81 2.91 4.43 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.53 2.25 10.08 2.79 1.81 2.91 4.43 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 10.03 2.25 9.48 3.95 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 6.27 6.74 5.41 2.25 6.14 2.79 1.81 2.91 7.99 5.87 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 18.76 7.1 6.74 11.19 2.25 7.16 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +3.82 19.53 7.1 6.74 11.19 2.25 6.14 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +3.02 19.53 7.1 6.74 11.19 2.25 7.93 2.79 1.81 2.91 7.99 14.9 60 1252 1 3739 1.22554203326529e-34 178.88534972369 11.072069215038 +5.13 19.53 7.1 6.74 18.57 9.99 10.08 2.79 1.81 2.91 4.43 14.9 48 1252 3 3739 2.58044343315991e-25 47.7480171723905 7.664082482531 +8.66 10.28 7.22 15.11 18.8 3.23 9.53 16.81 8.85 10.3 6.74 11.5 22 1252 7 3739 1.58822568308869e-08 9.37985553028365 2.097556978467 +5.13 16.11 16.06 6.74 11.19 6.57 10.08 2.79 1.81 2.91 7.99 14.9 44 1252 5 3739 3.0111763221621e-21 26.2647438328729 5.93328612772
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_barp_score.R Thu Sep 17 09:34:57 2020 +0000 @@ -0,0 +1,16 @@ +#!/usr/bin/env Rscript +args <- commandArgs(trailingOnly = TRUE) +file1=args[1] +scores=as.numeric(args[2]) +ofile=args[3] +bdata=read.table(file1,header=T) +bdata[,1:12]=bdata[,1:12]/rowSums(bdata[,1:12]) +rownames(bdata)=paste("#rank",c(1:nrow(bdata))) +col=c("#a6cee3","#1f78b4","#b2df8a","#33a02c","#fb9a99","#e31a1c","#fdbf6f","#ff7f00","#cab2d6","#6a3d9a","#ffff99","#b15928") +png(ofile,width=1800,height=800) +par(mar=c(10,4,4,25)) +X=barplot(t(bdata[1:scores,1:12]),horiz=F,col=col,legend.text=colnames(bdata)[1:12],args.legend = list(x = "right", bty="n", inset=c(-0.20,0), xpd = TRUE,cex=1.8),space=0.2,cex.axis=1.5,cex.names=2.5,las=2) +dev.off() + + +