Mercurial > repos > peter-waltman > ucsc_cluster_tools
comparison cluster.tools/consensus.clustering.xml @ 2:b442996b66ae draft
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author | peter-waltman |
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date | Wed, 27 Feb 2013 20:17:04 -0500 |
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1:e25d2bece0a2 | 2:b442996b66ae |
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1 <tool id="consensus_clustering" name="Consensus Clustering" force_history_refresh="True"> | |
2 <command interpreter="python">consensus.clustering.py | |
3 -d $dataset | |
4 -n ${direction} | |
5 -a ${method.algorithm} | |
6 #if $method.algorithm == 'hc' # -m ${method.hc_distance_metric} | |
7 -i ${method.innerLinkage} | |
8 #end if | |
9 #if $method.algorithm == 'pam' # -m ${method.pam_distance_metric} | |
10 #end if | |
11 #if $method.algorithm == 'km' # -m euclidean | |
12 #end if | |
13 -k ${kmax} | |
14 -r ${reps} | |
15 -f ${finalLinkage} | |
16 -o ${output} | |
17 -h $report | |
18 -p ${report.files_path} | |
19 | |
20 </command> | |
21 <inputs> | |
22 <param name="dataset" type="data" format='tabular' label="Data Set" help="Specify the data matrix (tab-delimited) to be clustered"/> | |
23 <param name="direction" type="select" label="Cluster Samples or Genes?" help="Specify the matrix dimension to cluster (see help below)"> | |
24 <option value="rows">Genes (rows)</option> | |
25 <option value="cols" selected="true">Samples (columns)</option> | |
26 </param> | |
27 | |
28 <conditional name='method'> | |
29 <param name="algorithm" type="select" label="Clustering Algorithm" help="Specify the cluster method to use (see help below)"> | |
30 <option value="hc">Hierarchical Clustering</option> | |
31 <option value="pam" selected='true'>Partioning around Medioids</option> | |
32 <option value="km">K-Means Clustering</option> | |
33 </param> | |
34 <when value='hc'> | |
35 <param name="hc_distance_metric" type="select" label="Distance Metric" help="Specify the distance metric to use (see help below)"> | |
36 <option value="cosine" selected='true'>Cosine</option> | |
37 <option value="abscosine">Absolute Cosine</option> | |
38 <option value="pearson">Pearson</option> | |
39 <option value="abspearson">Absolute Pearson</option> | |
40 <option value="spearman">Spearman</option> | |
41 <option value="kendall">Kendall</option> | |
42 <option value="euclidean">Euclidean</option> | |
43 <option value="maximum">Maximum</option> | |
44 <option value="manhattan">Manhattan (AKA city block)</option> | |
45 <option value="canberra">Canberra</option> | |
46 <option value="binary">Binary</option> | |
47 </param> | |
48 | |
49 <param name="innerLinkage" type="select" label="Linkage for inner HAC " help="Specify the linkage to use during the 'inner' hierarchcial clustering (see help below)"> | |
50 <option value="average">Average</option> | |
51 <option value="centroid">Centroid</option> | |
52 <option value="complete" selected='true'>Complete</option> | |
53 <option value="mcquitty">McQuitty</option> | |
54 <option value="median">Median</option> | |
55 <option value="single">Single</option> | |
56 <option value="ward">Ward</option> | |
57 </param> | |
58 </when> | |
59 <when value='pam'> | |
60 <param name="pam_distance_metric" type="select" label="Distance Metric" help="Specify the distance metric to use (see help below)"> | |
61 <option value="cosine" selected='true'>Cosine</option> | |
62 <option value="abscosine">Absolute Cosine</option> | |
63 <option value="pearson">Pearson</option> | |
64 <option value="abspearson">Absolute Pearson</option> | |
65 <option value="spearman">Spearman</option> | |
66 <option value="kendall">Kendall</option> | |
67 <option value="euclidean">Euclidean</option> | |
68 <option value="maximum">Maximum</option> | |
69 <option value="manhattan">Manhattan (AKA city block)</option> | |
70 <option value="canberra">Canberra</option> | |
71 <option value="binary">Binary</option> | |
72 </param> | |
73 </when> | |
74 </conditional> | |
75 <param name="finalLinkage" type="select" label="Final Linkage" help="Specify the linkage to use when clustering the consensus matrix (see help below)"> | |
76 <option value="average">Average</option> | |
77 <option value="centroid">Centroid</option> | |
78 <option value="complete" selected='true'>Complete</option> | |
79 <option value="mcquitty">McQuitty</option> | |
80 <option value="median">Median</option> | |
81 <option value="single">Single</option> | |
82 <option value="ward">Ward</option> | |
83 </param> | |
84 | |
85 | |
86 <param name="kmax" type="integer" label="K Max" value="10" help="Maximum number of K to analyze" /> | |
87 <param name="reps" type="integer" label="Repetitions" value="500" help="Number of Sample Permutations to Repeat"/> | |
88 | |
89 </inputs> | |
90 <outputs> | |
91 <data format="html" name="report" label="Consensus Clustering Report (HTML)"/> | |
92 <data format="rdata" name="output" label="Consensus Clustering Data (RData)"/> | |
93 </outputs> | |
94 <help> | |
95 .. class:: infomark | |
96 | |
97 **Perform Consensus Clustering (Cluster Samples) on a specified data set** | |
98 | |
99 ---- | |
100 | |
101 **Parameters** | |
102 | |
103 - **Data Set** - Specify the data matrix to be clustered. Data must be formated as follows: | |
104 | |
105 * Tab-delimited | |
106 * Use row/column headers | |
107 | |
108 - **Cluster Samples or Genes** - Specify the dimension of the matrix to cluster: | |
109 | |
110 * Rows (Genes) | |
111 * Columns (Samples) | |
112 | |
113 - **Clustering Algorithm** Specify the choice of algorithm to use. Choice of: | |
114 | |
115 * Hierarchical Clustering | |
116 * K-Means | |
117 | |
118 - **Distance Metric** Specify the choice of distance metric to use. Choice of: | |
119 | |
120 * Cosine (AKA uncentered pearson) | |
121 * Absolute Cosine (AKA uncentered pearson, absolute value) | |
122 * Pearson (pearson correlation) | |
123 * Absolute Pearson (pearson correlation, absolute value) | |
124 * Spearman (spearman correlation) | |
125 * Kendall (Kendall's Tau) | |
126 * Euclidean (euclidean distance) | |
127 * Maximum | |
128 * Manhattan (AKA city block) | |
129 * Canberra | |
130 * Binary | |
131 | |
132 - **Final Linkage** Specify the choice linkage to use when clustering Consensus Matrix. Choice of: | |
133 | |
134 * Average (see documentation for R's hclust function for explanation of choices) | |
135 * Single | |
136 * Complete | |
137 * Median | |
138 * Centroid | |
139 * McQuity | |
140 * Ward | |
141 | |
142 - **Inner Linkage** Specify the choice linkage to use when using HAC as clustering method. Same choices as 'Final Linkage' | |
143 | |
144 - **K Max** Specify the number to use for the largest K considered | |
145 | |
146 - **Repititions** Specify the number of 'bootstrap' repitions to perform to generate the consensus matrix | |
147 | |
148 </help> | |
149 </tool> |