<tool id="w4mclstrpeakpics" name="View Cluster_Peaks" version="0.98.1">
  <description>Visualize sample-cluster peaks</description>

  <requirements>
    <requirement type="package" >r-base</requirement>
    <requirement type="package" version="1.1_4">r-batch</requirement>
    <requirement type="package" version="1.4.2">r-reshape2</requirement>
    <requirement type="package" version="0.4_10">r-sqldf</requirement>
    <requirement type="package" version="0.98.1">w4mclstrpeakpics</requirement>
  </requirements>

  <stdio>
    <exit_code range="1:" level="fatal" />
  </stdio>


  <command detect_errors="exit_code"><![CDATA[
  Rscript $__tool_directory__/w4mclstrpeakpics_wrapper.R
  data_matrix_path '$dataMatrix_in'
  variable_metadata_path '$variableMetadata_in'
  sample_metadata_path '$sampleMetadata_in'
  sample_selector_column_name '$sampleSelectorColumnName'
  sample_selector_value '$sampleSelectorValue'
  output_pdf '$outputFigure'
  output_tsv '$outputTable'
  output_rdata '$outputRdata'
  r_package_archive $__tool_directory__/w4mclstrpeakpics_0.98.1.tar.gz
  ; echo exit code $?
  ]]></command>

  <inputs>
    <param name="dataMatrix_in" label="Data matrix file" type="data" format="tabular" help="variable x sample, decimal: '.', missing: NA, mode: numerical, separator: tab" />
    <param name="sampleMetadata_in" label="Sample metadata file" type="data" format="tabular" help="sample x metadata columns, separator: tab" />
    <param name="variableMetadata_in" label="Variable metadata file" type="data" format="tabular" help="variable x metadata columns, separator: tab" />
    <param name="sampleSelectorColumnName" label="Selector-column name" type="text" value = "sampleType" help="Name of column containing selector values." />
    <param name="sampleSelectorValue" label="Selector value" type="text" value = "pool" help="Value to match in sample-selector column." />
  </inputs>
  <outputs>
    <data name="outputTable" label="${tool.name}_${sampleSelectorValue}_table" format="tabular" ></data>
    <data name="outputFigure" label="${tool.name}_${sampleSelectorValue}_figure" format="pdf" ></data>
    <data name="outputRdata" label="${tool.name}_${sampleSelectorValue}_RData" format="rdata" ></data>
  </outputs>

  <tests>
    <test>
      <param name="dataMatrix_in" value="input_dataMatrix.tsv"/>
      <param name="sampleMetadata_in" value="input_sampleMetadata.tsv"/>
      <param name="variableMetadata_in" value="input_variableMetadata.tsv"/>
      <param name="sampleSelectorColumnName" value="sampleType"/>
      <param name="sampleSelectorValue" value="pool"/>
	  <output name="outputTable">
        <assert_contents>
          <has_text text="0.464572" />
          <has_text text="0.114304" />
          <has_text text="0.131016" />
          <has_text text="0.0701871" />
          <has_text text="0.0661764" />
          <has_text text="0.0384358" />
          <has_text text="0.0614973" />
          <has_text text="0.0260695" />
          <has_text text="0.0193850" />
          <has_text text="0.00835561" />
        </assert_contents>
	  </output>
    </test>
  </tests>



	<help>
		<![CDATA[

**Author**	Arthur Eschenlauer (University of Minnesota, esch0041@umn.edu)

--------------------------------------------------------------------------


**R package**

The *w4mclstrpeakpics* package is available from the Hegeman lab github repository (https://github.com/HegemanLab/w4mclstrpeakpics/releases).

-----------------------------------------------------------------------------------------------------------------------------------------


**Tool updates**

See the **NEWS** section at the bottom of this page

---------------------------------------------------

==================================
Visualize W4M sample-cluster peaks
==================================

-----------
Description
-----------

Produce a figure to assess the similarities and differences among peaks in a cluster of samples using XCMS-preprocessed data files as input.

-----------------
Workflow Position
-----------------

  - Upstream tool category: Preprocessing
  - Downstream tool categories: (Not applicable.)

----------
Motivation
----------

GC-MS1 and LC-MS1 experiments seek to resolve chemicals as features that have distinct chromatographic behavior and (after ionization) mass-to-charge ratio. 
Data for a sample are collected as MS intensities, each of which is associated with a position on a 2D plane with dimensions of m/z ratio and chromatographic retention time.
Ideally, features would be sufficiently reproducible from sample-run to sample-run to identify features that are commmon among samples and those that differ. 
However, the chromatographic retention time for a chemical can vary from one run to another.
In the Workflow4Metabolomics (W4M, [Giacomoni *et al.*, 2014]) "flavor" of Galaxy, the XCMS [Smith *et al.*, 2006] preprocessing tools provide for "retention time correction" to align features among samples.

In a typical GC-MS or LC-MS experiment, a pooled sample is repeatedly injected for quality control.
Since this is the same mixture for each injection, the identified peaks would be expected to be identical for all injections.
However, the parameters for peak-picking can exacerbate injection-to-injection variation in performance of the experimental apparatus.
This tool exists to assess the variation in the peaks picked among pooled samples, replicates, or indeed any cluster of samples.

-----------
Input files
-----------

+---------------------------+------------+
| File                      |   Format   |
+===========================+============+
|     Data matrix           |   tabular  |
+---------------------------+------------+
|     Sample metadata       |   tabular  |
+---------------------------+------------+
|     Variable metadata     |   tabular  |
+---------------------------+------------+


----------
Parameters
----------

Data matrix file
	| variable x sample **dataMatrix** (tabular separated values) file of the numeric data matrix, with . as decimal, and NA for missing values; the table must not contain metadata apart from row and column names; the row and column names must be identical to the rownames of the sample and variable metadata, respectively (see below)
	|

Sample metadata file
	| sample x metadata **sampleMetadata** (tabular separated values) file of the numeric and/or character sample metadata, with . as decimal and NA for missing values
	|

Variable metadata file
	| variable x metadata **variableMetadata** (tabular separated values) file of the numeric and/or character variable metadata, with . as decimal and NA for missing values
	|

Selector-column name (default = "sampleType")
	| column of W4M/XCMS sampleMetadata holding selector string values.
	|

Selector value (default = "pool")
	| value within selector column to identify samples for assessment.
	|

Include named classes (default = filter-out)
	| *filter-in* - include only the named sample classes
	| *filter-out* - exclude only the named sample classes
	|


Column that names the sample-class (default = 'class')
	| name of the column in sample metadata that has the values to be tested against the 'classes' input parameter
	|

Column that names the sample (default = 'sampleMetadata')
	| name of the column in sample metadata that has the name of the sample
	|


------------
Output files
------------


View Cluster_Peaks_<SelectorName>_figure
	| (PDF) the output figure, described below.
	|

View Cluster_Peaks_<SelectorName>_table
	| (tabular separated values) table of the values plotted in the upper-left graph in the output figure.
	|

View Cluster_Peaks_<SelectorName>_rdata
	| (R data) RData containing all processing and plotting intermediates..
	|


------
Graphs
------


**The "Feature Number and Likelihood" graph**

The upper left graph in the output figure shows the following:

* The X axis reflects the number of samples in which a given feature is present (“the prevalance of a feature among the samples”).
* For open circles, the Y axis reflects the number of features having the number of samples reflected on the X axis.
* For solid triangles, the Y axis reflects the relative likelihood of features having the number of samples reflected on the X axis, calculated as

	.. math:: \frac{(number\hspace{1 mm}of\hspace{1 mm}features) (number\hspace{1 mm}of\hspace{1 mm}samples\hspace{1 mm}per\hspace{1 mm}feature)}{maximum(number\hspace{1 mm}of\hspace{1 mm}samples\hspace{1 mm}per\hspace{1 mm}feature)}

Ideally, there would be an upward trend from left to right; if not, XCMS peak-picking parameters may need to be adjusted to suppress low-intensity “noise” peaks or to address peak-splitting.


**The "Peak Intensity" graph**

The lower left graph in the output figure presents the data in the upper figure without summarization, so that “the eye” can do the interpretation. It shows the following:

* The X axis reflects the number of samples in which a given feature is present (“the prevalance of a feature among the samples”).
* The Y axis reflects the intensity each sample for each feature having the number of samples reflected on the X axis.

Ideally, there would be an upward trend from left to right, with more points on the right; if not, XCMS peak-picking parameters may need to be adjusted to suppress low-intensity “noise” peaks or to address peak-splitting.


**The "Symbol area/intensity reflect ion intensity" graph**

The upper right graph in the output figure shows the following:

* The X axis reflects the corrected retention time for each feature shown.
* The Y axis reflects the m/z for each feature shown.
* Symbol area reflects intensity for a feature for one sample.
* Overlapping symbols make the overlapping area darker, so the area and darkness reflect the aggregated intensity of a feature. (It is doubtful that a densitometer would be able to recover aggregate intensities accurately from this graph, but philosophically that is how this graph is designed.)
* The graph is not designed to communicate prevalence of a feature among the samples, but the hue of the symbol reflects the prevalance, albeit subtly.

Consequently, if the graph has a lot of large, dark, blueish symbols for repeated runs of a pooled sample, there is strong evidence that the XCMS peak-picking parameters need adjustment to make peak-picking more consistent.


**The "Symbol size/shape reflects prevalence" graph**

By contrast with the area/intensity graph, lower right graph’s primary purpose is to communicate prevalence of a feature among the samples. It`shows the following:

* The X axis reflects the corrected retention time for each feature shown.
* The Y axis reflects the m/z for each feature shown.
* Symbol size and shape reflect the prevalence of a feature among the samples.
* “Vividness” of color reflects the aggregate intensity across all samples for a feature, in an attempt to draw attention to the more intense features.

Consequently, if the graph has a lot of small, vivid symbols for repeated runs of a pooled sample, there is strong evidence that the XCMS peak-picking parameters need adjustment to make peak-picking more consistent.


---------------
Working example
---------------

**Input files**

+-------------------+----------------------------------------------------------------------------------------------------------------+
| Input File        | Download from URL                                                                                              |
+===================+================================================================================================================+
| Data matrix       | https://raw.githubusercontent.com/HegemanLab/w4mclstrpeakpics/master/tests/testthat/input_dataMatrix.tsv       |
+-------------------+----------------------------------------------------------------------------------------------------------------+
| Sample metadata   | https://raw.githubusercontent.com/HegemanLab/w4mclstrpeakpics/master/tests/testthat/input_sampleMetadata.tsv   |
+-------------------+----------------------------------------------------------------------------------------------------------------+
| Variable metadata | https://raw.githubusercontent.com/HegemanLab/w4mclstrpeakpics/master/tests/testthat/input_variableMetadata.tsv |
+-------------------+----------------------------------------------------------------------------------------------------------------+

**Other input parameters**

+------------------------------------+-----------------+
| Input Parameter                    | Value           |
+====================================+=================+
| Selector-column name               | sampleType      |
+------------------------------------+-----------------+
| Selector value                     | pool            |
+------------------------------------+-----------------+



    ]]>
  </help>
  <citations>
    <citation type="doi">10.1021/ac051437y</citation>
    <citation type="doi">10.1093/bioinformatics/btu813</citation>
  </citations>
  <!--
     vim:noet:sw=4:ts=4
--> </tool>