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annotate mesmer.xml @ 0:53240d7c1fc5 draft

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planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/mesmer commit 5fb6aa9066c68d9972b3cc4be13503a952f952a5
author goeckslab
date Thu, 08 Sep 2022 15:17:30 +0000
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53240d7c1fc5 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/mesmer commit 5fb6aa9066c68d9972b3cc4be13503a952f952a5
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1 <tool id="mesmer" name="Mesmer" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="19.01">
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2 <description>Mesmer for whole-cell segmentation of multiplexed tissue imaging data</description>
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3
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4 <macros>
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5 <import>macros.xml</import>
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6 </macros>
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7
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8 <expand macro="requirements"/>
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9 <expand macro="version_cmd"/>
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11 <command detect_errors="exit_code"><![CDATA[
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12 ln -s '$nuclear_image' 'input.tif' &&
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13 @CMD_BEGIN@
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14 --output-directory ./
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15 --output-name 'mask.tif'
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16 --nuclear-image 'input.tif'
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17 --nuclear-channel $nuclear_channel
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18 --compartment $compartment
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19 --image-mpp $image_mpp
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20 $squeeze
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21
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22 #if $membrane_select.membrane_segment == "True":
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23 --membrane-image '$membrane_select.membrane_image'
53240d7c1fc5 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/mesmer commit 5fb6aa9066c68d9972b3cc4be13503a952f952a5
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24 --membrane-channel '$membrane_select.membrane_channel'
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25 #end if
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26 ]]></command>
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27
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28 <inputs>
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29 <param name="nuclear_image" type="data" format="tiff, ome.tiff" label="Image containing the nuclear marker(s)"/>
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30 <param name="nuclear_channel" type="integer" value="0" label="The numerical index of the channel(s) from nuclear-image"/>
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31 <param name="compartment" type="select" label="Compartment for segmentation prediction: ">
53240d7c1fc5 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/mesmer commit 5fb6aa9066c68d9972b3cc4be13503a952f952a5
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32 <option selected="true" value="whole-cell">Whole cell</option>
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33 <option value="nuclear">Nuclear</option>
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34 </param>
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35 <param name="image_mpp" type="float" value="0.5" label="Resolution of the image in microns-per-pixel"/>
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36 <param name="squeeze" type="boolean" truevalue="--squeeze" falsevalue="" checked="false" label="Whether to np.squeeze the outputs before saving"/>
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37 <conditional name="membrane_select">
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38 <param name="membrane_segment" type="select" label="Segment with Cell Membrane">
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39 <option selected="True" value="False">No</option>
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40 <option value="True">Yes</option>
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41 </param>
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42 <when value="True">
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43 <param name="membrane_image" type="data" format="tiff, ome.tiff" label="The path to an image containing the membrane marker(s)"/>
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44 <param name="membrane_channel" type="integer" value="0" label="The numerical index of the channel(s) from membrane-image"/>
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45 </when>
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46 <when value="False" />
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47 </conditional>
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48 </inputs>
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49 <outputs>
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50 <data format="tiff" name="mask" from_work_dir="mask.tif" label="${tool.name} on ${on_string}: Mask"/>
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51 </outputs>
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52 <tests>
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53 <test>
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54 <param name="nuclear_image" value="test.tiff" />
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55 <param name="compartment" value="nuclear" />
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56 <param name="membrane_select.membrane_segment" value="False" />
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57 <param name="image_mmp" value="0.65" />
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58 <param name="squeeze" value="--squeeze" />
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59 <output name="mask" ftype="tiff">
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60 <assert_contents>
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61 <has_size value="360000" delta="1000" />
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62 </assert_contents>
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63 </output>
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64 </test>
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65 </tests>
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66 <help><![CDATA[
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67 ------
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68 Mesmer
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69 ------
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70
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71 **Mesmer** is a DeepCell application that uses a pre-trained model for predicting nuclear and whole cell segmentation from multiplex tissue data.
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72
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73 **Inputs**
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74 1. a multiple tissue image that includes a nuclear marker and optionally cytoplasm/membrane markers
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75
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76 **Outputs**
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77 1. the nuclear or whole cell segmentation mask
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78 ]]></help>
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79 <expand macro="citations" />
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80 </tool>