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comparison 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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1 <tool id="mesmer" name="Mesmer" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="19.01">
2 <description>Mesmer for whole-cell segmentation of multiplexed tissue imaging data</description>
3
4 <macros>
5 <import>macros.xml</import>
6 </macros>
7
8 <expand macro="requirements"/>
9 <expand macro="version_cmd"/>
10
11 <command detect_errors="exit_code"><![CDATA[
12 ln -s '$nuclear_image' 'input.tif' &&
13 @CMD_BEGIN@
14 --output-directory ./
15 --output-name 'mask.tif'
16 --nuclear-image 'input.tif'
17 --nuclear-channel $nuclear_channel
18 --compartment $compartment
19 --image-mpp $image_mpp
20 $squeeze
21
22 #if $membrane_select.membrane_segment == "True":
23 --membrane-image '$membrane_select.membrane_image'
24 --membrane-channel '$membrane_select.membrane_channel'
25 #end if
26 ]]></command>
27
28 <inputs>
29 <param name="nuclear_image" type="data" format="tiff, ome.tiff" label="Image containing the nuclear marker(s)"/>
30 <param name="nuclear_channel" type="integer" value="0" label="The numerical index of the channel(s) from nuclear-image"/>
31 <param name="compartment" type="select" label="Compartment for segmentation prediction: ">
32 <option selected="true" value="whole-cell">Whole cell</option>
33 <option value="nuclear">Nuclear</option>
34 </param>
35 <param name="image_mpp" type="float" value="0.5" label="Resolution of the image in microns-per-pixel"/>
36 <param name="squeeze" type="boolean" truevalue="--squeeze" falsevalue="" checked="false" label="Whether to np.squeeze the outputs before saving"/>
37 <conditional name="membrane_select">
38 <param name="membrane_segment" type="select" label="Segment with Cell Membrane">
39 <option selected="True" value="False">No</option>
40 <option value="True">Yes</option>
41 </param>
42 <when value="True">
43 <param name="membrane_image" type="data" format="tiff, ome.tiff" label="The path to an image containing the membrane marker(s)"/>
44 <param name="membrane_channel" type="integer" value="0" label="The numerical index of the channel(s) from membrane-image"/>
45 </when>
46 <when value="False" />
47 </conditional>
48 </inputs>
49 <outputs>
50 <data format="tiff" name="mask" from_work_dir="mask.tif" label="${tool.name} on ${on_string}: Mask"/>
51 </outputs>
52 <tests>
53 <test>
54 <param name="nuclear_image" value="test.tiff" />
55 <param name="compartment" value="nuclear" />
56 <param name="membrane_select.membrane_segment" value="False" />
57 <param name="image_mmp" value="0.65" />
58 <param name="squeeze" value="--squeeze" />
59 <output name="mask" ftype="tiff">
60 <assert_contents>
61 <has_size value="360000" delta="1000" />
62 </assert_contents>
63 </output>
64 </test>
65 </tests>
66 <help><![CDATA[
67 ------
68 Mesmer
69 ------
70
71 **Mesmer** is a DeepCell application that uses a pre-trained model for predicting nuclear and whole cell segmentation from multiplex tissue data.
72
73 **Inputs**
74 1. a multiple tissue image that includes a nuclear marker and optionally cytoplasm/membrane markers
75
76 **Outputs**
77 1. the nuclear or whole cell segmentation mask
78 ]]></help>
79 <expand macro="citations" />
80 </tool>