Mercurial > repos > vijay > pancancer_apply_weights
annotate pancancer_apply_weights.xml @ 0:3543d3e66ecb draft default tip
"planemo upload for repository http://github.com/nvk747/papaa/galaxy/ commit 954b283ef7f82f59f55476a4b3a230d655187ac1"
author | vijay |
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date | Wed, 16 Dec 2020 23:30:39 +0000 |
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3543d3e66ecb
"planemo upload for repository http://github.com/nvk747/papaa/galaxy/ commit 954b283ef7f82f59f55476a4b3a230d655187ac1"
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1 <tool id="pancancer_apply_weights" name="PAPAA: PanCancer apply weights" version="@VERSION@"> |
3543d3e66ecb
"planemo upload for repository http://github.com/nvk747/papaa/galaxy/ commit 954b283ef7f82f59f55476a4b3a230d655187ac1"
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2 <description>apply weights</description> |
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3 <macros> |
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4 <import>macros.xml</import> |
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5 </macros> |
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6 <expand macro="requirements"/> |
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7 <expand macro="stdio"/> |
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8 <version_command><![CDATA['papaa_apply_weights.py' --version]]></version_command> |
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9 <command><![CDATA[ |
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10 mkdir 'classifier' && |
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11 ln -s '${pancan_classifier_summary}' 'classifier/classifier_summary.txt' && |
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12 ln -s '${pancan_classifier_coefficients}' 'classifier/classifier_coefficients.tsv' && |
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13 papaa_apply_weights.py |
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14 --classifier_summary 'classifier' |
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15 @INPUTS_BASIC@ |
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16 @INPUTS_COPY_NUMBER_CLASS_FILE_CONDITIONAL@ |
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17 > '${log}' |
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18 ]]></command> |
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19 <inputs> |
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20 <expand macro="inputs_basic"/> |
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21 <expand macro="inputs_copy_number_class_file_conditional"/> |
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22 <param argument="--classifier_summary" label="pancancer classifier summary" name="pancan_classifier_summary" optional="false" type="data" format="txt" help="classifer_summary.txt"/> |
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23 <param label="pancancer classifier coefficients" name="pancan_classifier_coefficients" optional="false" type="data" format="tabular" help="classifier_coefficients.tsv"/> |
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24 </inputs> |
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25 <outputs> |
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26 <data format="txt" name="log" label="${tool.name} on ${on_string} (Log)"/> |
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27 <data format="tabular" name="classifier_decisions" label="${tool.name} on ${on_string} (classifier_decisions.tsv)" from_work_dir="classifier/classifier_decisions.tsv"/> |
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28 </outputs> |
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29 <tests> |
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30 <test> |
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31 <param name="x_matrix" value="pancan_rnaseq_freeze_t1p.tsv.gz" ftype="tabular"/> |
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32 <param name="filename_mut" value="pancan_mutation_freeze_t1p.tsv.gz" ftype="tabular"/> |
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33 <param name="filename_mut_burden" value="mutation_burden_freeze.tsv" ftype="tabular"/> |
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34 <param name="filename_sample" value="sample_freeze.tsv" ftype="tabular"/> |
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35 <param name="copy_number" value="yes"/> |
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36 <param name="filename_copy_loss" value="copy_number_loss_status_t10p.tsv.gz" ftype="tabular"/> |
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37 <param name="filename_copy_gain" value="copy_number_gain_status_t10p.tsv.gz" ftype="tabular"/> |
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38 <param name="filename_cancer_gene_classification" value="cosmic_cancer_classification.tsv" ftype="tabular"/> |
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39 <param name="pancan_classifier_summary" value="classifier_summary.txt" ftype="txt"/> |
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40 <param name="pancan_classifier_coefficients" value="classifier_coefficients.tsv" ftype="tabular"/> |
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41 <output name="log" file="apply_weights_Log.txt"/> |
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42 <output name="classifier_decisions"> |
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43 <assert_contents> |
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44 <has_line line="SAMPLE_BARCODE	log10_mut	total_status	weight	AKT1	AKT1_gain	ERBB2	ERBB2_gain	KRAS	KRAS_gain	PIK3CA	PIK3CA_gain	PATIENT_BARCODE	DISEASE	SUBTYPE	hypermutated	include" /> |
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45 <has_n_columns n="17" /> |
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46 <has_n_lines n="90" /> |
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47 </assert_contents> |
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48 </output> |
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49 </test> |
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50 </tests> |
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51 <help><![CDATA[ |
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52 |
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53 **Pancancer_Aberrant_Pathway_Activity_Analysis scripts/papaa_apply_weights.py:** |
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54 |
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55 **Inputs:** |
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56 --classifier_summary String of the location of classifier_summary.txt file |
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57 --copy_number Supplement Y matrix with copy number events |
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58 --x_matrix Filename of features to use in model |
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59 --filename_mut_burden Filename of sample/gene mutations to use in model |
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60 --filename_mut_burden Filename of sample mutation burden to use in model |
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61 --filename_sample Filename of patient/samples to use in model |
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62 --filename_copy_loss Filename of copy number loss |
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63 --filename_copy_gain Filename of copy number gain |
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64 --filename_cancer_gene_classification Filename of cancer gene classification table |
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65 |
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66 **Outputs:** |
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67 Apply a logit transform on expression values (y = 1/(1+e^(-wX))) to output mutational probabilities. Generates "classifier_decisions.tsv" file which has scores/probabilities and other covariate information. The scores/probabilities will be used for gene ranking and variant specific classification. ]]> |
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68 </help> |
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69 <expand macro="citations" /> |
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70 </tool> |