view cluster.tools/determine.IPL.threshold.xml @ 1:dddfeedb85af draft

Uploaded

<tool id="determine_ipl_threshold" name="Determine IPL Threshold for Consensus Clustering" force_history_refresh="True">
    <command interpreter="python">determine.IPL.threshold.py
-d ${data_fname}
-f ${filter_type}
-p ${percentage_pass}
-s ${selection_criteria}
-h $report 
-r ${report.files_path}
-o ${output_rdata}
    </command>
    <inputs>
      <param name="data_fname" type="data" format="tabular" label="Paradigm Results File (contains both reals and nulls)"/>
      <param name="filter_type" type="select" label="Activity Filter" help="Specify the filter type to use (see help below)">
	<option value="active">Active</option>
	<option value="inactive">Inactive</option>
	<option value="modulated" selected='true' >Modulated</option>
      </param>
      <param name="percentage_pass" type="float" label="% of Samples Passing (value in 0-1 range; >= 1 to indicate exact number of samples)" value="0.33" help="Specify the percentage of samples thatmust pass the threshold (see help below)"/>
      <param name="selection_criteria" type="select" label="Selection Criteria" help="Specify the test statistic to use to select the threshold (see help below)">
	<option value="binomial">Binomial P-value</option>
	<option value="chisq">Chi-Squared P-value</option>
	<option value="max_diffs" selected='true' >Overall Max Number of Differences</option>
      </param>
    </inputs>
    <outputs>
      <data format="html" name="report" label="Determine IPL Threshold (HTML)"/>
      <data format="rdata" name="output_rdata"  label="Determine IPL Threshold (RData)"/>
    </outputs>
<help>

.. class:: infomark
     
**Determines a statistically sound threshold to use for a given IPL result**

**Parameters**
- **Paradigm Results File** Output from Paradigm (tab-delimited and contains both the 'real' and 'null' samples)

- **Activity Filter** Specify the filter type to use.  Choice of:

         * Activity -  Features must exceed the user-specified threshold
         * Inactivity -  Features must fall below the user-specified threshold
         * Modulated - Absolute value of the features must exceed the specified threshold

- **Percentage of Samples Passing** Percent of samples with an IPL that passes the threshold. Choice of:

         * Real Value in [0,1] - indicate the percentage of samples that pass the threshold
         * Integer Value       - indicate the exact number of samples that pass the threshold

- **Selection Criteria** Specify the test statistic to use to select the threshold.  Choice of:

         * Binomial P-value - Select the threshold with the largest -log p-value (calculated as a binomial)
         * Chi-Squared P-value - Select the threshold with the largest -log p-value (calculated as a Chi-squared)
         * Overall Max Number of Differences - Select the threshold with the largest overall number of differences between the real and null distributions
     

</help>
</tool>