forked from bgruening/galaxytools
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathmacros.xml
More file actions
86 lines (86 loc) · 6.16 KB
/
macros.xml
File metadata and controls
86 lines (86 loc) · 6.16 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
<macros>
<token name="@TOOL_VERSION@">0.2.17</token>
<token name="@VERSION_SUFFIX@">1</token>
<token name="@PROFILE@">24.1</token>
<xml name="requirements">
<requirements>
<requirement type="package" version="@TOOL_VERSION@">flexynesis</requirement>
<yield/>
</requirements>
</xml>
<xml name="edam">
<edam_topics>
<edam_topic>topic_0622</edam_topic>
<edam_topic>topic_3474</edam_topic>
<edam_topic>topic_2640</edam_topic>
</edam_topics>
<edam_operations>
<edam_operation>operation_3197</edam_operation>
<edam_operation>operation_2403</edam_operation>
<edam_operation>operation_2426</edam_operation>
</edam_operations>
</xml>
<token name="@CHECK_NON_COMMERCIAL_USE@"><![CDATA[
#if not $non_commercial_use
>&2 echo "this tool is only available for non commercial use";
exit 1;
#end if
]]></token>
<xml name="main_inputs">
<param name="train_clin" type="data" format="csv" label="Training clinical data"/>
<param name="test_clin" type="data" format="csv" label="Test clinical data"/>
<param name="train_omics_main" type="data" format="csv" label="Training omics data"/>
<param name="test_omics_main" type="data" format="csv" label="Test omics data"/>
<param name="assay_main" type="text" optional="true" label="What type of assay is your input?" help="This would be used as output name.">
<sanitizer invalid_char=" ">
<valid initial="string.letters">
<add value="_" />
</valid>
</sanitizer>
</param>
</xml>
<xml name="extra_inputs">
<param name="train_omics" type="data" optional="true" format="csv" label="Training omics data"/>
<param name="test_omics" type="data" optional="true" format="csv" label="Test omics data"/>
<param name="assay" type="text" optional="true" label="What type of assay is your input?" help="This would be used as output name." >
<sanitizer invalid_char=" ">
<valid initial="string.letters">
<add value="_" />
</valid>
</sanitizer>
</param>
</xml>
<xml name="advanced">
<section name="advanced" title="Advanced Options">
<param argument="--fusion_type" type="select" label="Fusion method" help="How to fuse the omics layers?">
<option value="intermediate">intermediate</option>
<option value="early">early</option>
</param>
<param argument="--finetuning_samples" type="integer" min="0" value="0" label="Number of samples from the test dataset to use for fine-tuning the model." help="Set to 0 to disable fine-tuning." />
<param argument="--variance_threshold" type="float" min="0" max="100" value="1" label="Variance threshold (as percentile) to drop low variance features." help="Set to 0 for no variance filtering." />
<param argument="--correlation_threshold" type="float" min="0" max="1" value="0.8" label="Correlation threshold to drop highly redundant features." help="Set to 1 for no redundancy filtering." />
<param argument="--subsample" type="integer" min="0" value="0" label="Downsample training set to randomly drawn N samples for training." />
<param argument="--features_min" type="integer" min="0" value="500" label="Minimum number of features to retain after feature selection." />
<param argument="--features_top_percentile" type="float" min="0" max="100" value="20" label="Top percentile features (among the features remaining after variance filtering and data cleanup) to retain after feature selection." />
<param argument="--log_transform" type="boolean" truevalue="--log_transform True" falsevalue="" checked="false" label="Whether to apply log-transformation to input data matrices" />
<param argument="--early_stop_patience" type="integer" min="-1" value="10" label="How many epochs to wait when no improvements in validation loss are observed." help="Set to -1 to disable early stopping." />
<param argument="--hpo_iter" type="integer" min="1" value="100" label="Number of iterations for hyperparameter optimisation." />
<param argument="--val_size" type="float" min="0.0" max="1" value="0.2" label="Proportion of training data to be used as validation split"/>
<param argument="--hpo_patience" type="integer" min="0" value="10" label="How many hyperparameter optimisation iterations to wait for when no improvements are observed." help="Set to 0 to disable early stopping." />
<param argument="--use_cv" type="boolean" truevalue="--use_cv" falsevalue="" checked="false" label="Cross validation" help="If set, a 5-fold cross-validation training will be done. Otherwise, a single training on 80 percent of the dataset is done. " />
<param argument="--use_loss_weighting" type="boolean" truevalue="--use_loss_weighting True" falsevalue="" checked="true" label="Whether to apply loss-balancing using uncertainty weights method." />
<param argument="--evaluate_baseline_performance" type="boolean" truevalue="--evaluate_baseline_performance" falsevalue="" checked="false" label="Enable modeling also with Random Forest + SVMs to see the performance of off-the-shelf tools on the same dataset." />
<param argument="--feature_importance_method" type="select" label="which method(s) to use to compute feature importance scores.">
<option value="Both" selected="true">Both</option>
<option value="IntegratedGradients">IntegratedGradients</option>
<option value="GradientShap">GradientShap</option>
</param>
<param argument="--disable_marker_finding" type="boolean" truevalue="--disable_marker_finding" falsevalue="" checked="false" label="Disable marker discovery after model training." />
</section>
</xml>
<xml name="citations">
<citations>
<citation type="doi">10.1101/2024.07.16.603606</citation>
</citations>
</xml>
</macros>