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planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/palom commit 08d9f2d59c26e67a162d75ae6e8b5fa734ab7b3c
author goeckslab
date Tue, 06 Sep 2022 21:15:56 +0000
parents 69f8e01b2e17
children
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1:69f8e01b2e17 2:e30f622ef2c3
1 <tool id="palom" name="palom" version="2021.12.0.1"> 1 <tool id="palom" name="palom" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
2 <description>Piecewise alignment for layers of mosaics. A tool for registering whole-slide images with different IHC stainings</description> 2 <description>Piecewise alignment for layers of image mosaics.</description>
3
3 <macros> 4 <macros>
4 <import>macros.xml</import> 5 <import>macros.xml</import>
5 </macros> 6 </macros>
7
6 <expand macro="requirements" /> 8 <expand macro="requirements" />
9
7 <command detect_errors="exit_code"><![CDATA[ 10 <command detect_errors="exit_code"><![CDATA[
8 11
9 ln -s "$reference_image" ./ref.svs && 12 ln -s '$reference_image' './ref.svs' &&
10 13
11 ln -s "$channels" ./channels.csv && 14 ln -s '$channels' './channels.csv' &&
12 15
13 #for $i in $moving_images: 16 #for $i in $moving_images:
14 ln -s "$i" "${i.name}" && 17 ln -s '$i' '${i.name}' &&
15 #end for 18 #end for
16 19
17 python "$script" 20 python '$script'
18 21
19 ]]></command> 22 ]]></command>
20 <configfiles> 23 <configfiles>
21 <configfile name = "script"> 24 <configfile name = "script">
22 import os 25 import os
23 import pathlib 26 import pathlib
24 import pandas as pd 27 import pandas as pd
28 import matplotlib.pyplot as plt
25 import palom 29 import palom
26 from palom.cli.svs import run_palom 30 from palom.cli.svs import run_palom
27 31
32 plt.switch_backend('agg')
33
28 cwd = os.getcwd() 34 cwd = os.getcwd()
29 35
30 ref_img = pathlib.Path(os.path.join(cwd,"ref.svs")) 36 ref_img = pathlib.Path(os.path.join(cwd,'ref.svs'))
31 37
32 images = [ref_img] 38 images = [ref_img]
33 channels = ["hematoxylin"] 39 channels = ['hematoxylin']
34 modes = ["hematoxylin"] 40 modes = ['hematoxylin']
35 41
36 #for $i in $moving_images: 42 #for $i in $moving_images:
37 img = pathlib.Path("${i.name}") 43 img = pathlib.Path('${i.name}')
38 images.append(img) 44 images.append(img)
39 #end for 45 #end for
40 46
41 channel_df = pd.read_csv(os.path.join(cwd, "channels.csv")) 47 channel_df = pd.read_csv(os.path.join(cwd, 'channels.csv'))
42 channel_df = channel_df.astype({'channel':'string'}) 48 channel_df = channel_df.astype({'channel':'string'})
43 channels += list(channel_df['channel']) 49 channels += list(channel_df['channel'])
44 modes += list(channel_df['mode']) 50 modes += list(channel_df['mode'])
45 51
46 pixel_size = None 52 pixel_size = None
47 53
48 #if $pixel_size: 54 #if $pixel_size:
49 pixel_size = float($pixel_size) 55 pixel_size = float($pixel_size)
50 #end if 56 #end if
51 57
52 level = 0 58 level = int($level)
59 downscale_factor = int($downscale_factor)
53 60
54 #if $level: 61 output_path = pathlib.Path(os.path.join(cwd, 'registered.ome.tiff'))
55 level = int($level)
56 #end if
57
58 output_path = pathlib.Path(os.path.join(cwd, "registered.ome.tiff"))
59 62
60 qc_path = output_path.parent / 'qc' 63 qc_path = output_path.parent / 'qc'
61 64
62 os.mkdir(qc_path) 65 os.mkdir(qc_path)
63 66
66 img_modes = modes, 69 img_modes = modes,
67 pixel_size = pixel_size, 70 pixel_size = pixel_size,
68 channel_names = channels, 71 channel_names = channels,
69 output_path = output_path, 72 output_path = output_path,
70 qc_path = qc_path, 73 qc_path = qc_path,
71 level = level 74 level = level,
75 downscale_factor = downscale_factor
72 ) 76 )
73 </configfile> 77 </configfile>
74 </configfiles> 78 </configfiles>
75 <inputs> 79 <inputs>
76 <param name="reference_image" type="data" format="tiff" label="Hematoxylin reference image" help="An H+E image in .svs format"/> 80 <param name="reference_image" type="data" format="tiff" label="Hematoxylin reference image" help=".svs format image to align to"/>
77 <param name="moving_images" type="data_collection" label="Moving Images (data collection)" help="A collection of svs-format images to align to the reference image"/> 81 <param name="moving_images" type="data_collection" label="Moving Images (data collection)" help="A collection of .svs format images to align to the reference image"/>
78 <param name="channels" type="data" label="Channel and mode dataframe" help="A CSV file with 'channel' and 'mode' columns, with a row corresponding to each moving image"/> 82 <param name="channels" type="data" label="Channel and mode dataframe" help="A CSV file with 'channel' and 'mode' columns, with a row for each moving image"/>
79 <param name="pixel_size" type="float" optional="true" label="Pixel Size" help="defaults to px size of reference image"/> 83 <param name="pixel_size" type="float" optional="true" label="Pixel size (optional)" help="defaults to px size of reference image"/>
80 <param name="level" type="integer" optional="true" label="Level" help="pyramid level, defaults to 0 (lowest level)"/> 84 <param name="level" type="integer" value="0" label="Pyramid level" help="pyramid level, defaults to 0 (lowest level)"/>
85 <param name="downscale_factor" type="integer" value="2" label="Pyramid downscale factor" help="Default of 2 makes pyramid downscaling compatible with Avivator and Vitessce"/>
81 </inputs> 86 </inputs>
82 <outputs> 87 <outputs>
83 <collection name="qc_plots" type="list" label="${tool.name}: qc_plots"> 88 <collection name="qc_plots" type="list" label="${tool.name}: qc_plots">
84 <discover_datasets pattern="__name_and_ext__" directory="qc" ext="png" visible="false"/> 89 <discover_datasets pattern="__name_and_ext__" directory="qc" ext="png" visible="false"/>
85 </collection> 90 </collection>
86 <data name="registered" from_work_dir="registered.ome.tiff" format="ome.tiff"/> 91 <data name="registered" from_work_dir="registered.ome.tiff" format="ome.tiff"/>
87 </outputs> 92 </outputs>
93 <tests>
94 <test>
95 <param name="reference_image" value="test_ref.svs"/>
96 <param name="moving_images">
97 <collection type="list">
98 <element name="m1" value="test_moving.svs"/>
99 </collection>
100 </param>
101 <param name="channels" value="test_channels.csv"/>
102 <param name="level" value="1"/>
103 <output_collection name="qc_plots" type="list">
104 <element name="01-test_moving.svs" ftype="png">
105 <assert_contents>
106 <has_size value="277000" delta="100000" />
107 </assert_contents>
108 </element>
109 </output_collection>
110 <output name="registered" ftype="ome.tiff">
111 <assert_contents>
112 <has_size value="59000000" delta="20000000" />
113 </assert_contents>
114 </output>
115 </test>
116 </tests>
88 <help><![CDATA[ 117 <help><![CDATA[
89 # PALOM 118 ------
90 registration of whole-slide images with different IHC stainings 119 PALOM
120 ------
121 **PALOM** performs registration of whole-slide images with different IHC stainings.
122 **Inputs**
123 1.) Reference image for aligning image mosiacs to
124 2.) A collection of images to be aligned
125 3.) File describing the channels/targets
91 126
92 Tool github: https://github.com/Yu-AnChen/palom 127 **Outputs**
128 1.) Registered image as ome.tiff
129 2.) Colleciton of QC plots
93 130
94 # Main developer 131 More details on Github: https://github.com/Yu-AnChen/palom
95 132
96 Yu-An Chen (https://github.com/Yu-AnChen)
97 ]]></help> 133 ]]></help>
98 <expand macro="citations" /> 134 <expand macro="citations" />
99 </tool> 135 </tool>