Mercurial > repos > malex > secimtools
comparison bland_altman_plot.xml @ 1:2e7d47c0b027 draft
"planemo upload for repository https://malex@toolshed.g2.bx.psu.edu/repos/malex/secimtools"
author | malex |
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date | Mon, 08 Mar 2021 22:04:06 +0000 |
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children | caba07f41453 |
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0:b54326490b4d | 1:2e7d47c0b027 |
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1 <tool id="secimtools_bland_altman_plot" name="Bland-Altman (BA) Plot" version="@WRAPPER_VERSION@"> | |
2 <description>- Create pairwise BA plots for outlier detection.</description> | |
3 <macros> | |
4 <import>macros.xml</import> | |
5 </macros> | |
6 <expand macro="requirements" /> | |
7 <command detect_errors="exit_code"><![CDATA[ | |
8 bland_altman_plot.py | |
9 --input $input | |
10 --design $design | |
11 --ID $uniqID | |
12 --figure $ba_plots | |
13 --flag_dist $outlier_dist_plots | |
14 --flag_sample $flag_sample | |
15 --flag_feature $flag_feature | |
16 --resid_cutoff $resid_cutoff | |
17 --sample_flag_cutoff $sample_cutoff | |
18 --feature_flag_cutoff $feature_cutoff | |
19 --prop_feature $proportion_of_features | |
20 --prop_sample $proportion_of_samples | |
21 | |
22 #if $group | |
23 --group $group | |
24 | |
25 #if $processOnly: | |
26 --process_only "$processOnly" | |
27 #end if | |
28 #end if | |
29 ]]></command> | |
30 <inputs> | |
31 <param name="input" type="data" format="tabular" label="Wide Dataset" help="Input your tab-separated wide format dataset. If file is not tab-separated see TIP below."/> | |
32 <param name="design" type="data" format="tabular" label="Design File" help="Input your design file (tab-separated). Note you need a 'sampleID' column. If not tab separated see TIP below."/> | |
33 <param name="uniqID" size="30" type="text" value="" label="Unique Feature ID" help="Name of the column in your wide dataset that contains unique feature identifiers."/> | |
34 <param name="resid_cutoff" type="integer" size="30" value="3" label="Outlier Cutoff" help="Residual cutoff value, this value will flag samples with residuals ≥ this cutoff value."/> | |
35 <param name="sample_cutoff" type="float" size="30" value="0.2" min="0" max="1" label="Sample Flag Cutoff" help="Flag a sample as 1 if the proportion of features within a sample that are outliers exceeds this cutoff. [Number between 0-1]."/> | |
36 <param name="feature_cutoff" type="float" size="30" value="0.05" min="0" max="1" label="Feature Flag Cutoff" help="Flag a feature as 1 if the proportion of times this feature was identified as an outlier exceeds this cutoff. [Number between 0-1]."/> | |
37 <param name="group" type="text" size="30" value="" optional="true" label="Group/Treatment [Optional]" help="Name of the column in your Design File that contains group classifications."/> | |
38 <param name="processOnly" size="30" type="text" value="" optional="true" label="Group Name [Optional]" help="Name of the group(s) that you want to process. Separate multiple group names with spaces (e.g. RC,control,treatment). Leave blank to process all groups. Requires the group parameter."/> | |
39 </inputs> | |
40 <outputs> | |
41 <data format="pdf" name="ba_plots" label= "${tool.name} on ${on_string}: BA plot" /> | |
42 <data format="pdf" name="outlier_dist_plots" label= "${tool.name} on ${on_string}: Distribution"/> | |
43 <data format="tabular" name="flag_sample" label= "${tool.name} on ${on_string}: Flag Sample"/> | |
44 <data format="tabular" name="flag_feature" label= "${tool.name} on ${on_string}: Flag Feature"/> | |
45 <data format="tabular" name="proportion_of_features" label= "${tool.name} on ${on_string}: Proportion of Feature"/> | |
46 <data format="tabular" name="proportion_of_samples" label= "${tool.name} on ${on_string}: Proportion of Samples"/> | |
47 </outputs> | |
48 <tests> | |
49 <test> | |
50 <param name="input" value="ST000006_data.tsv"/> | |
51 <param name="design" value="ST000006_design.tsv"/> | |
52 <param name="uniqID" value="Retention_Index" /> | |
53 <param name="group" value="White_wine_type_and_source" /> | |
54 <output name="ba_plots" file="ST000006_bland_altman_plot_with_group_figure.pdf" compare="sim_size" delta="10000" /> | |
55 <output name="outlier_dist_plots" file="ST000006_bland_altman_plot_with_group_flag_distribution.pdf" compare="sim_size" delta="10000" /> | |
56 <output name="flag_sample" file="ST000006_bland_altman_plot_with_group_flag_sample.tsv" /> | |
57 <output name="flag_feature" file="ST000006_bland_altman_plot_with_group_flag_feature.tsv" /> | |
58 <output name="prop_feature" file="ST000006_bland_altman_plot_with_group_proportion_feature.tsv" /> | |
59 <output name="prop_sample" file="ST000006_bland_altman_plot_with_group_proportion_sample.tsv" /> | |
60 </test> | |
61 </tests> | |
62 <help><![CDATA[ | |
63 | |
64 @TIP_AND_WARNING@ | |
65 | |
66 **Tool Description** | |
67 | |
68 The Bland-Altman plot (BA-Plot) is used to look at the concordance of data between pairs of samples, particularly between replicates. | |
69 The script generates BA-plots for all pairwise combinations of samples. | |
70 If the Group/Treatment column and group name(s) in that column are provided then BA-Plots are generated only for pairwise combinations within the specified Group -- group name combination. | |
71 In addition to generating the BA-plots, a linear regression fit is calculated between the values that correspond to the pair of samples to identify (flag) any unusual outlying values. | |
72 The flags produced by the regression fit are used to generate distribution plots and text files for (i) each sample (column) and for (ii) each feature (row). | |
73 | |
74 | |
75 -------------------------------------------------------------------------------- | |
76 | |
77 **Input** | |
78 | |
79 - Two input datasets are required. | |
80 | |
81 @WIDE@ | |
82 | |
83 **NOTE:** The sample IDs must match the sample IDs in the Design File | |
84 (below). Extra columns will automatically be ignored. | |
85 | |
86 @METADATA@ | |
87 | |
88 @UNIQID@ | |
89 | |
90 | |
91 **Outlier Cutoff – flagging values** | |
92 | |
93 - Residual cutoff value, this value will flag samples with residuals ≥ than this cutoff value. | |
94 | |
95 (1) If the magnitude of the residuals from the linear regression on the BA-plot exceeds the user-defined threshold, then a value is flagged as an outlier. This cutoff can be adjusted by the user, the default is 3. | |
96 | |
97 (2) If a value is identified as a leverage point using Cook's D with a p-value cutoff of 0.5, then the value is flagged. This cannot be adjusted. | |
98 | |
99 (3) If a value is identified as a leverage point using the DFFITS technique it is also flagged. This cannot be adjusted. | |
100 | |
101 **Sample Flag Cutoff – flagging samples** | |
102 | |
103 - Flag a sample as 1 if the proportion of features within a sample that are outliers exceeds this cutoff. [Number between 0-1]. | |
104 | |
105 **Feature Flag Cutoff – flagging features** | |
106 | |
107 - Flag a feature as 1 if the proportion of times this feature was identified as an outlier exceeds this cutoff. [Number between 0-1]. | |
108 | |
109 @GROUP@ | |
110 | |
111 **Group ID** | |
112 | |
113 - Name of the group(s) that you want to process. Separate multiple groupIDs with spaces. Leave blank to process all groups. Requires the group parameter. | |
114 | |
115 -------------------------------------------------------------------------------- | |
116 | |
117 **Output** | |
118 | |
119 This tool outputs four (or five) different files depending on the input settings: | |
120 (1) a PDF file containing BA-plots and scatterplots for each pair of samples | |
121 (2) a PDF file containing histograms of the most flagged features and samples | |
122 (3) two TSV files containing flags: one for samples and one for features | |
123 (4) if a grouping variable name is specified in the input, a TSV file containing flags for each group is also generated. | |
124 (5) two TSV files containing (i) the proportion of features flagged per sample and (ii) the proportion of samples flagged per feature. | |
125 If a sample (or feature) is flagged, the user should consider removing it from further analysis. | |
126 | |
127 ]]></help> | |
128 <expand macro="citations"/> | |
129 </tool> |