Mercurial > repos > galaxyp > diffacto
diff diffacto.xml @ 0:3cc7ce0822a1 draft default tip
"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/diffacto commit 507bb20a2c246bb0a1a0c7dae1555a851730e4a6"
| author | galaxyp |
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| date | Mon, 21 Jun 2021 12:50:54 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/diffacto.xml Mon Jun 21 12:50:54 2021 +0000 @@ -0,0 +1,267 @@ +<tool id="diffacto" name="Diffacto" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" python_template_version="3.5"> + <description>Comparative Protein Abundance from Covariation of Peptide Abundances</description> + <macros> + <token name="@TOOL_VERSION@">1.0.6</token> + <token name="@VERSION_SUFFIX@">0</token> + </macros> + <requirements> + <requirement type="package" version="@TOOL_VERSION@">diffacto</requirement> + </requirements> + <command detect_errors="exit_code"><![CDATA[ + tr '\t' ',' < '$input' > input.csv && + diffacto + -i input.csv + #if $db + -db '$db' + #end if + #if $samples + -samples '$samples' + #end if + -reference '$reference' + #if $normalize + -normalize $normalize + #end if + #if $farms_mu + -farms_mu $farms_mu + #end if + #if $farms_alpha + -farms_alpha $farms_alpha + #end if + -min_samples $min_samples + -impute_threshold $impute_threshold + -cutoff_weight $cutoff_weight + $use_unique + #if $scale == 'log2' + -log2 True + #else + -log2 False + #end if + $fast + -out '$output' + #if $mcfdr + -mc_out '$mc_out' + #end if + #if $loadings + -loadings_out '$loadings_out' + #end if + ]]></command> + <inputs> + <param name="input" argument="-i" type="data" format="tabular,csv" label="Peptides abundances"> + <help><![CDATA[ + Peptides abundances in tabular or csv format. + <ul> + <li>The first row is column headers and should contain the sample name for each sample column. </li> + <li>The first column should contain unique peptide sequences. </li> + <li><i>Optionally, the second column may be ProteinID assignments, else the <b>Protein database</b> input is required.</i></li> + <li>Each remaining column is a sample column with numeric abundance values.</li> + <li>Missing values should be empty instead of zeros.</li> + </ul> + ]]></help> + </param> + <param argument="-db" type="data" format="fasta" label="Protein database" optional="true" + help="Required if the Peptide abundances input does not have Protein IDs in the second column"/> + <param argument="-samples" type="data" format="tabular" label="Sample Groups" optional="true"> + <help><![CDATA[ + <i>Optional: By default, each Sample column in Peptide abundances is treated as a singleton group.</i> + <br> + Groups the samples from the Peptides abundance input for comparison. + Each sample column from Peptides abundance input should be on a line with 2 columns: + <ol> + <li>Sample name for header line of the Peptides abundance input.</li> + <li>Group Name assignemnt for the sample</li> + </ol> + ]]></help> + </param> + <param argument="-reference" type="text" value="" label="Reference sample groups" optional="true"> + <help><![CDATA[ + <i>Optional: By default, Diffacto uses the average of all samples/groups as the reference.</i> + <br> + Names of sample groups <i>(separated by semicolon)</i> treated as the comparison reference. + <ul> + <li>If a Sample Groups input was used, the reference names should be Group names from column 2.</li> + <li>Otherwise, the reference names should be Sample names from the Peptides abundance column header line.</li> + </ul> + ]]></help> + </param> + <param name="scale" argument="-log2" type="select" label="Peptides abundance scale"> + <option value="linear">linear</option> + <option value="log2">log2</option> + </param> + <param argument="-normalize" type="select" label="Sample-wise normalization" optional="true"> + <option value="average">average</option> + <option value="median">median</option> + <option value="GMM">GMM</option> + </param> + <param argument="-farms_mu" type="float" value="0.1" min="0.0" max="1.0" optional="true" label="Hyperparameter mu" + help="Hyperparameter mu (default: 0.1)"/> + <param argument="-farms_alpha" type="float" value="0.1" min="0.0" max="1.0" optional="true" label="Hyperparameter alpha" + help="Hyperparameter weight of prior probability (default: 0.1)"/> + <param argument="-min_samples" type="integer" value="1" min="1" label="Minimum samples for peptide" + help="Minimum number of samples peptides needed to be quantified in"/> + <param argument="-impute_threshold" type="float" value="0.99" min="0.1" max="1.0" label="Minimum fraction of missing values in the group" + help="Impute missing values if missing fraction is larger than the threshold."/> + <param argument="-cutoff_weight" type="float" value="0.5" min="0." max="1.0" label="Peptide cutoff weight" + help="Peptides weighted lower than the cutoff will be excluded."/> + <param argument="-use_unique" type="boolean" truevalue="-use_unique True" falsevalue="" checked="false" label="Use unique peptides only"/> + <param argument="-fast" type="boolean" truevalue="-fast True" falsevalue="" checked="false" label="Allow early termination in EM calculation when noise is sufficiently small."/> + <param name="mcfdr" argument="-mc_out" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Perform Monte Carlo FDR simulation"/> + <param name="loadings" argument="-loadings_out" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Output Protein Peptide loadings file"/> + </inputs> + <outputs> + <data name="output" format="tabular" label="${tool.name} on ${on_string}: Protein Abundance"> + <actions> + <action name="comment_lines" type="metadata" default="1" /> + <action name="column_names" type="metadata" default="Protein,N.Pept,Q.Pept,S/N,P(PECA)" /> + </actions> + </data> + <data name="mc_out" format="tabular" label="${tool.name} on ${on_string}: MC FDR"> + <filter>mcfdr == True</filter> + <actions> + <action name="comment_lines" type="metadata" default="1" /> + <action name="column_names" type="metadata" default="Protein,P(MC),MCFDR" /> + </actions> + </data> + <data name="loadings_out" format="tabular" label="${tool.name} on ${on_string}: Protein Peptide loading"> + <filter>loadings == True</filter> + <actions> + <action name="comment_lines" type="metadata" default="1" /> + <action name="column_names" type="metadata" default="Protein,Peptide,Loading" /> + </actions> + </data> + </outputs> + <tests> + <test> + <param name="input" ftype="csv" value="HBY20Mix.peptides.csv"/> + <param name="db" ftype="fasta" value="UP000002311_559292.fasta"/> + <param name="samples" ftype="tabular" value="HBY20Mix.samples.lst"/> + <output name="output"> + <assert_contents> + <has_text text="P19097" /> + </assert_contents> + </output> + </test> + <test> + <param name="input" ftype="tabular" value="HBY20Mix.peptides.tsv"/> + <param name="db" ftype="fasta" value="UP000002311_559292.fasta"/> + <param name="samples" ftype="tabular" value="HBY20Mix.samples.lst"/> + <output name="output"> + <assert_contents> + <has_text text="P19097" /> + </assert_contents> + </output> + </test> + + <test> + <param name="input" ftype="csv" value="iPRG.novo.pep.csv"/> + <param name="samples" ftype="tabular" value="iPRG.samples.lst"/> + <param name="min_samples" value="2"/> + <output name="output"> + <assert_contents> + <has_text text="FAS2" /> + </assert_contents> + </output> + </test> + <test> + <param name="input" ftype="csv" value="iPRG.novo.pep.csv"/> + <param name="samples" ftype="tabular" value="iPRG.samples.lst"/> + <param name="min_samples" value="4"/> + <param name="use_unique" value="True"/> + <param name="mcfdr" value="True"/> + <output name="output"> + <assert_contents> + <has_text text="FAS2" /> + </assert_contents> + </output> + <output name="mc_out"> + <assert_contents> + <has_text text="FAS2" /> + </assert_contents> + </output> + </test> + + </tests> + <help><![CDATA[ +**Diffacto** + +Diffacto_ quantifies comparative protein abundance from the covariation of peptide abundances. + +Diffacto_ applies factor analysis to extract the covariation of peptides' abundances. The method enables a weighted geometrical average summarization and automatic elimination of incoherent peptides, which may result from suboptimal digestion or being partially modified, and are not representative of the protein concentration. + +**Inputs** + + - **Peptides abundances** *in tabular or csv format* + + - The first row is column headers and should contain the sample name for each sample column. + - The first column should contain unique peptide sequences. + - *Optionally, the second column may be Protein ID assignments, else the* **Protein database** *input is required.* + - Each remaining column is a sample column with numeric abundance values. + - Missing values should be empty instead of zeros. + - Example: + + ============ ========== ========= ========= ========= ========= + sequences Protein Sample1-A Sample1_B Sample2_A Sample2_B + ============ ========== ========= ========= ========= ========= + AAATAAMTK EF3A 127.35209 142.58217 135.89206 162.54500 + AAATTGEWDK PDC1 100.35922 114.68676 922.60617 833.97955 + LPVLLADACCSR HSP72;PDC1 120.21570 194.99594 977.48321 219.23281 + AAEEAGVTDVK FAS2 442.67501 457.52266 448.52837 424.15980 + ============ ========== ========= ========= ========= ========= + + + - **Protein database** *(optional)* + + - The Protein database in fasta format that has protein seqeunces containing the peptides. + - Required if the **Peptides abundances** input does not have a second column containing Protein ID assignments + + + - **Sample Groups** *(optional)* + + - First column has the sample name + - Second column has the group name + - Example: + + ========= == + Sample1-A S1 + Sample1_B S1 + Sample2_A S2 + Sample2_B S2 + ========= == + + +**Outputs** + + - **Protein Abundance** + + ======= ====== ====== =================== =================== ================== ================== + Protein N.Pept Q.Pept S/N P(PECA) S1 S2 + ======= ====== ====== =================== =================== ================== ================== + EF3A 2 2 -2.874362404756714 0.2608189432601452 463172795.59269696 489796576.81520355 + FAS2 6 4 -0.5901265476375578 0.8395809777778386 52093246.23323742 53280470.3811749 + PDC1 3 2 6.634988423694361 0.25491030879514676 203769831.79809052 174641994.14231393 + ======= ====== ====== =================== =================== ================== ================== + + - **FDR Estimate from Monte Carlo Simulation** *(optional)* + + ======= =================== =================== + Protein P(MC) MCFDR + ======= =================== =================== + EF3A 0.1419053964023984 0.5287482885321804 + FAS2 0.9867109634551495 0.9132662960822688 + PDC1 0.3338088445078459 0.5287482885321804 + ======= =================== =================== + + - **Protein Peptide Loadings** *(optional)* + + ======= =========== =================== + EF3A AAATAAMTK 0.5287482885321804 + FAS2 AAEEAGVTDVK 0.9132662960822688 + PDC1 AAATTGEWDK 0.5287482885321804 + ======= =========== =================== + +.. _Diffacto: https://github.com/statisticalbiotechnology/diffacto + + ]]></help> + <citations> + <citation type="doi">10.1074/mcp.O117.067728</citation> + </citations> +</tool>