Mercurial > repos > rnateam > blockclust

annotate blockclust.xml @ 13:dbb6ee3179bc draft default tip

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/blockclust commit 6957c96f98dea265503f4e126d4aaa6f8c2e1d2e
author bgruening
date Sat, 04 Nov 2023 10:07:58 +0000
parents aab6cf87b40a
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dbb6ee3179bc planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/blockclust commit 6957c96f98dea265503f4e126d4aaa6f8c2e1d2e
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1 <tool id="blockclust" name="BlockClust" version="1.1.1">
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2 <description>efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles</description>
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3 <requirements>
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4 <requirement type="package" version="1.1.1">blockclust</requirement>
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5 </requirements>
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6 <version_command>blockclust.py -v</version_command>
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7 <command detect_errors="aggressive"><![CDATA[
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8 export BLOCKCLUST_DATA_PATH=\$(dirname \$(which blockclust.py))/../share/blockclust_data &&
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9
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10 #if str($tool_mode.operation) == "pre":
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11 ln -s '$tool_mode.reads_bam' reads.bam &&
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12 ln -f -s '${$tool_mode.reads_bam.metadata.bam_index}' reads.bam.bai &&
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13 blockclust.py
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14 -m PRE -bam reads.bam
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15 -tbed '$tags_bed'
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16 #elif str($tool_mode.operation) == "analysis":
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17 #set $outputdir = $clusters.files_path
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18 blockclust.py
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19 -o ./
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20 -m ANALYSIS
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21 -f "\$BLOCKCLUST_DATA_PATH/blockclust.config"
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22 -t $tool_mode.input_bbo
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23 -a "\$BLOCKCLUST_DATA_PATH/$tool_mode.reference/${tool_mode.reference}.accept.bed"
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24 -r "\$BLOCKCLUST_DATA_PATH/$tool_mode.reference/${tool_mode.reference}.reject.bed"
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25 #if $tool_mode.nochr:
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26 -nochr
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27 #end if
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28 #if str($tool_mode.pred.enable_pred) == "yes":
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29 -c
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30 -cm $tool_mode.pred.pred_mode
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31 -md "\$BLOCKCLUST_DATA_PATH/models"
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32 #end if
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33 #elif str($tool_mode.operation) == "post":
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34 blockclust.py
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35 -m POST
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36 -cbed '$tool_mode.clusters_bed'
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37 -cs '$tool_mode.cmsearch_out'
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38 -tab '$tool_mode.sim_tab_in'
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39 -rfam "\$BLOCKCLUST_DATA_PATH/rfam_map.txt"
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40 -o ./
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41 #end if
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42 ]]>
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43 </command>
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44 <inputs>
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45 <conditional name="tool_mode">
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46 <param name="operation" type="select" label="Select mode of operation">
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47 <option value="pre">Pre-processing </option>
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48 <option value="analysis">Clustering and classification</option>
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49 <option value="post">Post-processing</option>
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50 </param>
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51 <when value="pre">
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52 <param name="reads_bam" type="data" format="bam" label="BAM file containing alignments" />
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53 </when>
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54 <when value="analysis">
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55 <param name="input_bbo" type="data" format="tabular" label="Input blockgroups file" />
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56 <param name="reference" type="select" label="Select reference genome">
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57 <option value="hg19">Human (hg19)</option>
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58 <option value="mm10">Mouse (mm10)</option>
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59 <option value="dm3">Fly (dm3)</option>
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60 <option value="rheMac3">Monkey (rheMac3)</option>
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61 <option value="panTro4">Chimp (panTro4)</option>
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62 <option value="xenTro3">Frog (xenTro3)</option>
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63 <option value="celWS235">C. elegans (celWS235)</option>
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64 <option value="tair10">Arabidopsis thaliana (tair10)</option>
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65 </param>
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66 <param name="nochr" type="boolean" label="My input files have no 'chr' for chromosome names" checked="False"/>
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67 <conditional name="pred">
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68 <param name="enable_pred" type="select" label="Would you like to perform classification?">
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69 <option value="no">No</option>
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70 <option value="yes">Yes</option>
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71 </param>
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72 <when value="yes">
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73 <param name="pred_mode" type="select" label="Mode of classification">
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74 <option value="MODEL">Model based</option>
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75 <option value="NEAREST">Nearest neighbour</option>
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76 </param>
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77 </when>
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78 </conditional>
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79 </when>
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80 <when value="post">
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81 <param name="cmsearch_out" type="data" format="tabular" label="Output of cmsearch tool" />
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82 <param name="clusters_bed" type="data" format="bed" label="BED file containing clusters (output of BlockClust)" />
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83 <param name="sim_tab_in" type="data" format="tabular" label="Pairwise similarities file" />
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84 </when>
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85 </conditional>
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86 </inputs>
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87
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88 <outputs>
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89 <data format="bed" name="tags_bed" label="BlockClust: BAM to BED on ${on_string}">
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90 <filter>tool_mode["operation"]=="pre"</filter>
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91 </data>
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92 <data format="pdf" name="hclust_plot" from_work_dir="hclust_tree.pdf" label="BlockClust: Hierarchical clustering plot on ${on_string}" >
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93 <filter>tool_mode["operation"]=="analysis"</filter>
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94 </data>
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95 <data format="bed" name="clusters" from_work_dir="mcl_clusters/all_clusters.bed" label="BlockClust: BED of predicted clusters on ${on_string}">
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96 <filter>tool_mode["operation"]=="analysis"</filter>
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97 </data>
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98 <data format="bed" name="model_based_pred_bed" from_work_dir="model_based_predictions.txt" label="BlockClust: Model based predictions BED on ${on_string}">
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99 <filter>
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100 ((
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101 tool_mode["operation"] == 'analysis' and
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102 tool_mode["pred"]["enable_pred"] == "yes" and
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103 tool_mode["pred"]["pred_mode"] == "MODEL"
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104 ))
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105 </filter>
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106 </data>
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107 <data format="bed" name="nearest_neighbour_pred_bed" from_work_dir="nearest_neighbour_predictions.txt" label="BlockClust: Nearest neighbor predictions BED on ${on_string}">
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108 <filter>
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109 ((
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110 tool_mode["operation"] == 'analysis' and
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111 tool_mode["pred"]["enable_pred"] == "yes" and
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112 tool_mode["pred"]["pred_mode"] == "NEAREST"
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113 ))
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114 </filter>
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115 </data>
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116 <data format="tabular" name="sim_tab_out" from_work_dir="discretized.gspan.tab" label="BlockClust: Pairwise similarities on ${on_string}">
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117 <filter>tool_mode["operation"]=="analysis"</filter>
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118 </data>
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119 <data format="pdf" name="cluster_dist" from_work_dir="cluster_distribution.pdf" label="BlockClust: Cluster distribution on ${on_string}" >
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120 <filter>tool_mode["operation"]=="post"</filter>
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121 </data>
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122 <data format="pdf" name="cluster_hclust" from_work_dir="hclust_tree_clusters.pdf" label="BlockClust: Hierarchical clustering plot of cluster centroids on ${on_string}" >
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123 <filter>tool_mode["operation"]=="post"</filter>
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124 </data>
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125 </outputs>
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126 <tests>
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127 <!-- Test: PRE mode -->
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128
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129 <test expect_num_outputs="1">
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130 <param name="operation" value="pre"/>
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131 <param name="reads_bam" value="test.bam"/>
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132 <output name="tags_bed">
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133 <assert_contents>
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134 <has_text_matching expression="chr6\t26555497\t26555527\ttag_10\|1\|19\t0.052632\t\+" />
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135 <has_text_matching expression="chr11\t122017275\t122017297\ttag_30\|1\|3\t0.333333\t-" />
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136 </assert_contents>
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137 </output>
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138 </test>
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139
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140 <!-- Test: Clustering only -->
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141 <test expect_num_outputs="3">
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142 <param name="operation" value="analysis"/>
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143 <param name="input_bbo" value="test.tabular"/>
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144 <param name="reference" value="hg19"/>
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145 <param name="enable_pred" value="no"/>
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146 <output name="clusters">
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147 <assert_contents>
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148 <has_text_matching expression="chr1\t173833959\t173834043\t10:snoRNA_CD-box:blockgroup_939:cluster_1\t451.50\t-" />
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149 <has_text_matching expression="chr13\t92003008\t92003075\t8:miRNA:blockgroup_256:cluster_3\t2950.50\t\+" />
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150 </assert_contents>
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151 </output>
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152 </test>
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153
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154 <!-- Test: Model based prediction -->
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155
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156 <test expect_num_outputs="4">
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157 <param name="operation" value="analysis"/>
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158 <param name="input_bbo" value="test.tabular"/>
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159 <param name="reference" value="hg19"/>
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160 <param name="enable_pred" value="yes"/>
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161 <param name="pred_mode" value="MODEL"/>
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162 <output name="model_based_pred_bed">
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163 <assert_contents>
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164 <has_text_matching expression="chr2\t203211000\t203211097\tpredicted_tRNA\t284.07\t-" />
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165 </assert_contents>
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166 </output>
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167 </test>
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168
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169 <!-- Test: Nearest neighbour based prediction -->
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170
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171 <test expect_num_outputs="4">
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172 <param name="operation" value="analysis"/>
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173 <param name="input_bbo" value="test.tabular"/>
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174 <param name="reference" value="hg19"/>
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175 <param name="enable_pred" value="yes"/>
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176 <param name="pred_mode" value="NEAREST"/>
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177 <output name="nearest_neighbour_pred_bed">
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178 <assert_contents>
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179 <has_text_matching expression="chr2\t203211000\t203211097\tpredicted_tRNA\t284.07\t-" />
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180 </assert_contents>
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181 </output>
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182 </test>
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183
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184 </tests>
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185 <help>
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186 <![CDATA[
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187
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188 .. class:: infomark
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189
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190 **What it does**
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191
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192 BlockClust is an efficient approach to detect transcripts with similar
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193 processing patterns. We propose a novel way to encode expression profiles
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194 in compact discrete structures, which can then be processed using
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195 fast graph-kernel techniques. BlockClust allows both clustering and
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196 classification of small non-coding RNAs.
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197
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198 BlockClust runs in three operating modes:
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199
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200 1) Pre-processing - converts given mapped reads (BAM) into BED file of tags
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201
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202 2) Clustering and classification - of given input blockgroups (output of blockbuster tool) as explained in the original paper.
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203
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204 3) Post-processing - plots for overview of predicted clusters.
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205
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206 For a thorough analysis of your data, we suggest you to use complete blockclust workflow, which contains all three modes of operation.
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207
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208 **Inputs**
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209
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210 BlockClust input files are dependent on the mode of operation:
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211
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212 1. Pre-processing mode:
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213 * Binary Sequence Alignment Map (BAM) file
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214
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215 2. Clustering and classification:
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216 * A blockgroups file generated by blockbuster tool
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217 * Select reference genome
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218
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219 3. Post-processing:
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220 * Output of cmsearch, searched clusters generated by BlockClust against Rfam
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221 * BED file containing clusters generated by BlockClust
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222 * Pairwise similarities of blockgroups generated by BlockClust
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223
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224 **Outputs**
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225
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226 1. Pre-processing mode:
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227 * BED file of tags with expressions
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228
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229 2. Clustering and classification:
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230 * Hierarchical clustering plot of all input blockgroups by their similarity
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231 * Pairwise similarities of all input blockgroups
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232 * BED file containing predicted clusters
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233 * BED file containing prediction of blockgroups by pre-compiled SVM binary classification model.
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234
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235 3. Post-processing:
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236 * Plot of distribution of ncRNA families per predicted cluster (overview of cluster precissions). The annotation of ncRNA families are retrieved by searching cluster instances against Rfam database.
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237 * Hierarchical clustering made out of centroids of each BlockClust predicted cluster
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238
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239
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