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10
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1 <tool id="oncoenrichr_wrapper" name="oncoEnrichR" version="1.5.1.1">
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2
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2 <description>Cancer-dedicated gene set interpretation</description>
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3 <requirements>
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10
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4 <container type="docker">sigven/oncoenrichr:1.5.1.1</container>
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2
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5 </requirements>
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9
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6 <environment_variables>
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7 <environment_variable name="XDG_CACHE_HOME">\$_GALAXY_JOB_TMP_DIR</environment_variable>
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8 </environment_variables>
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2
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9 <command detect_errors="aggressive"><![CDATA[
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10 #if $query_set.query_choice.query_input == "text"
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11 echo $query_set.query_choice.query_text | sed 's/__cn__/\n/g' > query_text.csv &&
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12 #set input_file = './query_text.csv'
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13 #else if $query_set.query_choice.query_input == "file"
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14 ln -s $query_set.query_choice.query_file "$query_set.query_choice.query_file.element_identifier" &&
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15 #set input_file = './' + str($query_set.query_choice.query_file.element_identifier)
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16 #end if
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17
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18 #set background_file = ''
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19 #if $fun_enrich.custom_bgset.def_background
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20 #if $fun_enrich.custom_bgset.bg_choice.bg_source == "text"
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21 echo $fun_enrich.custom_bgset.bg_choice.bg_enrich_text | sed 's/__cn__/\n/g' > custom_bgset.csv &&
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22 #set background_file = './custom_bgset.csv'
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23 #else if $fun_enrich.custom_bgset.bg_choice.bg_source == "file" and $fun_enrich.custom_bgset.bg_choice.bg_enrich_file
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24 ln -s $fun_enrich.custom_bgset.bg_choice.bg_enrich_file background_text.csv &&
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25 #set background_file = './custom_bgset.csv'
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26 #else
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27 #set background_file = ''
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28 #end if
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29 #end if
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30
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31 R -e 'suppressPackageStartupMessages(library(oncoEnrichR));
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32 suppressWarnings(load(system.file("internal_db", "oedb.rda", package = "oncoEnrichR")));
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8
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33 gene_data <- read.csv("$input_file", strip.white = TRUE);
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2
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34 oe_report <- oncoEnrichR::onco_enrich(
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35 query = gene_data[[1]],
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36 oeDB = oedb,
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37 #if $query_set.query_id_type
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38 query_id_type = "$query_set.query_id_type",
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39 #end if
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40 ignore_id_err = $query_set.ignore_id_err,
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41
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42 #if $report_metadata.project_title
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43 project_title = "$report_metadata.project_title",
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44 #end if
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45 #if $report_metadata.project_owner
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46 project_owner = "$report_metadata.project_owner",
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47 #end if
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48 #if $report_metadata.project_description
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49 project_description = "$report_metadata.project_description",
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50 #end if
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51
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52 show_enrichment = $modules.show_enrichment,
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53 show_ppi = $modules.show_ppi,
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54 show_disease = $modules.show_disease,
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55 show_cancer_hallmarks = $modules.show_cancer_hallmarks,
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56 show_drug = $modules.show_drug,
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57 show_aberration = $modules.show_aberration,
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58 show_coexpression = $modules.show_coexpression,
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59 show_subcell_comp = $modules.show_subcell_comp,
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60 show_complex = $modules.show_complex,
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3
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61 show_domain = $modules.show_domain,
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2
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62 show_fitness = $modules.show_fitness,
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63 show_ligand_receptor = $modules.show_ligand_receptor,
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64 show_regulatory = $modules.show_regulatory,
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3
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65 show_prognostic = $modules.show_prognostic,
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66 show_unknown_function = $modules.show_unknown_function,
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2
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67 show_synleth = $modules.show_synleth,
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68
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69 #if $background_file
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70 bgset = read.csv("$background_file", strip.white = TRUE)[[1]],
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71 #if $fun_enrich.custom_bgset.bg_enrich_id_type
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72 bgset_id_type = "$fun_enrich.custom_bgset.bg_enrich_id_type",
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73 #end if
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74 #if $fun_enrich.custom_bgset.bg_enrich_description
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75 bgset_description = "$fun_enrich.custom_bgset.bg_enrich_description",
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76 #end if
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77 #else
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78 bgset = NULL,
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79 #end if
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80
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3
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81 #if $fun_enrich.enrichment_p_value_cutoff
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82 enrichment_p_value_cutoff = $fun_enrich.enrichment_p_value_cutoff,
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2
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83 #end if
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3
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84 #if $fun_enrich.enrichment_p_value_adj
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85 enrichment_p_value_adj = "$fun_enrich.enrichment_p_value_adj",
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86 #end if
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87 #if $fun_enrich.enrichment_q_value_cutoff
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88 enrichment_q_value_cutoff = $fun_enrich.enrichment_q_value_cutoff,
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2
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89 #end if
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3
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90 #if $fun_enrich.enrichment_min_geneset_size
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91 enrichment_min_geneset_size = $fun_enrich.enrichment_min_geneset_size,
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2
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92 #end if
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3
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93 #if $fun_enrich.enrichment_max_geneset_size
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94 enrichment_max_geneset_size = $fun_enrich.enrichment_max_geneset_size,
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2
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95 #end if
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3
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96 enrichment_plot_num_terms = $fun_enrich.enrichment_plot_num_terms,
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97 enrichment_simplify_go = $fun_enrich.enrichment_simplify_go,
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98
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2
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99
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100 #if $protein_interactions.ppi_add_nodes
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101 ppi_add_nodes = $protein_interactions.ppi_add_nodes,
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102 #end if
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3
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103 #if $protein_interactions.ppi_string_min_score
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104 ppi_string_min_score = $protein_interactions.ppi_string_min_score,
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2
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105 #end if
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3
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106 #if $protein_interactions.ppi_biogrid_min_evidence
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107 ppi_biogrid_min_evidence = $protein_interactions.ppi_biogrid_min_evidence,
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108 #end if
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109 ppi_show_drugs = $protein_interactions.ppi_show_drugs,
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110 ppi_show_isolated_nodes = $protein_interactions.ppi_show_isolated_nodes,
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111 ppi_node_shadow = $protein_interactions.ppi_node_shadow,
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112
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3
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113 #if $subcellular_compartments.subcellcomp_min_confidence
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114 subcellcomp_min_confidence = $subcellular_compartments.subcellcomp_min_confidence,
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2
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115 #end if
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3
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116 #if $subcellular_compartments.subcellcomp_min_channels
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117 subcellcomp_min_channels = $subcellular_compartments.subcellcomp_min_channels,
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2
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118 #end if
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3
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119 #if $fitness.fitness_max_score
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120 fitness_max_score = $fitness.fitness_max_score,
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121 #end if
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122 subcellcomp_show_cytosol = $subcellular_compartments.subcellcomp_show_cytosol,
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2
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123 #if $disease.show_top_diseases_only
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124 show_top_diseases_only = $disease.show_top_diseases_only,
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125 #end if
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126
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3
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127 regulatory_min_confidence = "$regulatory.regulatory_min_confidence",
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128 galaxy = TRUE
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129 );
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130
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8
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131 oncoEnrichR::write(report = oe_report, oeDB = oedb, file = "$report1", format = "html", embed_resources = F, extra_files_path = "$report1.extra_files_path", overwrite = T, ignore_file_extension = T);
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132 oncoEnrichR::write(report = oe_report, oeDB = oedb, file = "$report2", format = "excel", overwrite = T, ignore_file_extension = T)' 2>&1
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2
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133
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134 ]]></command>
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135 <inputs>
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136 <section title="" name=""/>
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137 <section name="query_set" title="Query gene set" expanded="true">
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138 <conditional name="query_choice">
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139 <param name="query_input" type="select" multiple="false" display="radio"
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140 label="Query gene set: do you want to upload a file OR paste into a text box?">
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141 <option value="text">Text field</option>
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142 <option value="file">From file</option>
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143 </param>
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144 <when value="text">
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145 <param type="text" name="query_text" label="Query gene set identifiers (one per line)" area="true"/>
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146 </when>
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147 <when value="file">
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148 <param name="query_file" type="data" format="txt" label="Query gene set identifiers" multiple="false"/>
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149 </when>
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150 </conditional>
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151 <param name="query_id_type" type="select" label="Query identifier type" display="radio" multiple="false">
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152 <option value="symbol">Primary gene symbol (HGNC) - e.g. KRAS</option>
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153 <option value="uniprot_acc">UniProt accession - e.g. P01116</option>
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154 <option value="entrezgene">NCBI Entrez gene identifier - e.g. 3845</option>
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155 <option value="ensembl_gene">Ensembl gene identifier - e.g. ENSG00000133703</option>
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156 <option value="ensembl_mrna">Ensembl transcript identifier - e.g. ENST00000311936</option>
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157 <option value="ensembl_protein">Ensembl protein identifier - e.g. ENSP00000308495</option>
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8
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158 <option value="refseq_transcript_id">RefSeq mRNA identifier - e.g. NM_004985</option>
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2
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159 <option value="refseq_protein">RefSeq protein identifier - e.g. NP_004976</option>
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160 </param>
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161 <param name="ignore_id_err" type="boolean" label="Ignore erroneous idenfiers" truevalue="T" falsevalue="F" checked="true"/>
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162 </section>
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163
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164 <section title="" name=""/>
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165 <section name="report_metadata" title="Project metadata and output settings" expanded="true">
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166 <param type="text" name="report_name" label="Output filename (prefix)" value="Report"/>
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167 <param type="text" name="project_title" label="Project title" />
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168 <param type="text" name="project_owner" label="Project owner" />
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169 <param type="text" name="project_description" label="Project description" area="true"/>
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170 </section>
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171
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172 <section title="" name=""/>
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173 <section name="modules" title="Analysis modules included in the report" expanded="true">
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174 <param name="show_disease" type="boolean" label="Gene-cancer associations" truevalue="T" falsevalue="F" checked="true"/>
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2
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175 <param name="show_enrichment" type="boolean" label="Gene functional enrichment" truevalue="T" falsevalue="F" checked="true"/>
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176 <param name="show_ppi" type="boolean" label="Protein-protein interaction network" truevalue="T" falsevalue="F" checked="true"/>
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177 <param name="show_regulatory" type="boolean" label="Regulatory (TF-target) interactions" truevalue="T" falsevalue="F" checked="false"/>
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178 <param name="show_ligand_receptor" type="boolean" label="Ligand-receptor interactions" truevalue="T" falsevalue="F" checked="false"/>
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2
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179 <param name="show_cancer_hallmarks" type="boolean" label="Cancer hallmark associations" truevalue="T" falsevalue="F" checked="true"/>
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180 <param name="show_drug" type="boolean" label="Drug-target associations" truevalue="T" falsevalue="F" checked="true"/>
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8
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181 <param name="show_aberration" type="boolean" label="Tumor aberration frequencies" truevalue="T" falsevalue="F" checked="false"/>
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182 <param name="show_coexpression" type="boolean" label="Tumor co-expression patterns" truevalue="T" falsevalue="F" checked="false"/>
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2
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183 <param name="show_subcell_comp" type="boolean" label="Subcellular localizations" truevalue="T" falsevalue="F" checked="true"/>
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184 <param name="show_complex" type="boolean" label="Protein complex memberships" truevalue="T" falsevalue="F" checked="true"/>
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185 <param name="show_domain" type="boolean" label="Protein domain frequencies" truevalue="T" falsevalue="F" checked="false"/>
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2
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186 <param name="show_fitness" type="boolean" label="Gene fitness effects" truevalue="T" falsevalue="F" checked="true"/>
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187 <param name="show_synleth" type="boolean" label="Predicted synthetic lethality interactions" truevalue="T" falsevalue="F" checked="true"/>
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8
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188 <param name="show_unknown_function" type="boolean" label="Genes of poorly defined function" truevalue="T" falsevalue="F" checked="false"/>
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3
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189 <param name="show_prognostic" type="boolean" label="Prognostic cancer associations" truevalue="T" falsevalue="F" checked="true"/>
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2
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190 </section>
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191
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192 <section title="" name=""/>
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193 <section name="fun_enrich" title="Options - gene functional enrichment">
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2
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194 <conditional name="custom_bgset">
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195 <param name="def_background" type="boolean" label="Define custom background set (all annotated protein-coding genes by default)" truevalue="T" falsevalue="F" checked="false"/>
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196 <when value="T">
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197 <conditional name="bg_choice">
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198 <param name="bg_source" type="select" display="radio"
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199 label="Custom background gene set: do you want to upload a file OR paste into a text box?">
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200 <option value="text">Text field</option>
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201 <option value="file">From file</option>
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202
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203 </param>
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204 <when value="file">
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205 <param type="data" format="txt" name="bg_enrich_file" label="Custom background gene set" optional="true" multiple="false"/>
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206 </when>
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207 <when value="text">
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208 <param type="text" name="bg_enrich_text" label="Custom background gene set identifiers (one per line):" area="true"/>
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209 </when>
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210 </conditional>
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211
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212 <param type="select" name="bg_enrich_id_type" label="Custom background identifier type" display="radio" multiple="false">
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213 <option value="symbol">Primary gene symbol (HGNC) - e.g. KRAS</option>
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214 <option value="uniprot_acc">UniProt accession - e.g. P01116</option>
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215 <option value="entrezgene">NCBI Entrez gene identifier - e.g. 3845</option>
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216 <option value="ensembl_gene">Ensembl gene identifier - e.g. ENSG00000133703</option>
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217 <option value="ensembl_mrna">Ensembl transcript identifier - e.g. ENST00000311936</option>
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218 <option value="ensembl_protein">Ensembl protein identifier - e.g. ENSP00000308495</option>
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8
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219 <option value="refseq_transcript_id">RefSeq mRNA identifier - e.g. NM_004985</option>
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2
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220 <option value="refseq_protein">RefSeq protein identifier - e.g. NP_004976</option>
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221 </param>
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222 <param type="text" name="bg_enrich_description" label="Custom background gene set description" value="Custom background description"/>
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223 </when>
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224 </conditional>
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225
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3
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226 <param name="enrichment_p_value_cutoff" type="float" label="P-value cutoff for enrichment tests (clusterProfiler)" value="0.05"/>
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227 <param name="enrichment_p_value_adj" type="select" label="P-value adjustment method (clusterProfiler)">
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228 <option value="BH">Benjamini-Hochberg</option>
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229 <option value="holm">Holm</option>
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230 <option value="hochberg">Hochberg</option>
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231 <option value="hommel">Hommel</option>
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232 <option value="bonferroni">Bonferroni</option>
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233 <option value="BY">Benjamini-Yekutieli</option>
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2
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234 <option value="fdr">fdr</option>
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235 <option value="none">none</option>
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236 </param>
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3
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237 <param name="enrichment_q_value_cutoff" type="float" label="Q-value cutoff for enrichment tests to report as significant (clusterProfiler)" value="0.2"/>
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238 <param name="enrichment_min_geneset_size" type="integer" label="Minimum number of genes annotated by ontology term for testing (clusterProfiler)" value="10"/>
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239 <param name="enrichment_max_geneset_size" type="integer" label="Maximum number of genes annotated by ontology term for testing (clusterProfiler)" value="500"/>
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240 <param name="enrichment_simplify_go" type="boolean" label="Simplify GO enrichment results by removal of redundant terms (recommended)" truevalue="T" falsevalue="F" checked="true"/>
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241 <param name="enrichment_plot_num_terms" type="integer" label="Number of top enriched Gene Ontology terms (max) to show in enrichment barplot" min="10" max="30" value="20"/>
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2
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242 </section>
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243
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244 <section title="" name=""/>
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3
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245 <section name="fitness" title="Options - gene fitness scores">
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246 <param name="fitness_max_score" type="float" label="Maximum loss-of-fitness score (Bayes Factor from BAGEL) for genes retrieved from Project Score" value="-2" min="-5" max="0"/>
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2
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247 </section>
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248 <section title="" name=""/>
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3
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249 <section name="protein_interactions" title="Options - protein-protein interaction network">
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250 <param name="ppi_network_type" type = "select" label="STRING: type of retrieved network interactions">
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251 <option value="functional">functional</option>
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252 <option value="physical">physical</option>
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253 </param>
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254 <param name="ppi_string_min_score" type="float" label="STRING: minimum confidence score for interactions to be included in network" value="0.9" min="0.4" max="1"/>
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255 <param name="ppi_biogrid_min_evidence" type="integer" label="BioGRID: Minimum number of evidence support for interactions to be included in network" value="3" min="2" max="10"/>
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256 <param name="ppi_add_nodes" type="integer" label="Addition of interacting non-queryset proteins to the protein-protein interaction network (STRING/BioGRID)" value="30" min="0" max="50"/>
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257 <param name="ppi_show_drugs" type="boolean" label="Attach anti-cancer drugs in protein-protein interaction network (STRING/BioGRID)" truevalue="T" falsevalue="F" checked="false"/>
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258 <param name="ppi_show_isolated_nodes" type="boolean" label="Show isolated nodes in protein-protein interaction network (STRING/BioGRID)" truevalue="T" falsevalue="F" checked="false"/>
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259 <param name="ppi_node_shadow" type="boolean" label="Add shadow to nodes in protein-protein interaction network" truevalue="T" falsevalue="F" checked="true"/>
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2
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260 </section>
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261 <section title="" name=""/>
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3
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262 <section name="regulatory" title="Options - regulatory interactions">
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263 <param name="regulatory_min_confidence" type="select" label = "Minimum confidence level of regulatory interactions included (DoRothEA - A:highest, D:lowest)">
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2
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264 <option value="D">D</option>
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265 <option value="C">C</option>
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266 <option value="B">B</option>
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267 <option value="A">A</option>
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268 </param>
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269 </section>
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270 <section title="" name=""/>
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271
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3
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272 <section name="subcellular_compartments" title="Options - Subcellular compartment annotations">
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273 <param name="subcellcomp_min_confidence" type="integer" label="Minimum confidence level for subcellular compartment annotations" value="3" min="3" max="5"/>
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274 <param name="subcellcomp_min_channels" type="integer" label="Minimum number of channel (Text Mining, Experimental, Knowledge) support for annotations" value="1" min="1" max="3"/>
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275 <param name="subcellcomp_show_cytosol" type="boolean" label="Show cytosol annotations (very common localization) in subcellular heatmap " truevalue="T" falsevalue="F" checked="false"/>
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2
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276 </section>
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277 <section title="" name=""/>
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278
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279 <section name="disease" title="Options - Disease associations">
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280 <param type="boolean" name="show_top_diseases_only" label="Show top disease assocations only" truevalue="T" falsevalue="F" checked="true"/>
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281 </section>
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282
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283 </inputs>
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284 <outputs>
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285 <data format="xlsx" name="report2" label="$report_metadata.report_name - xlsx"/>
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286 <data format="html" name="report1" label="$report_metadata.report_name - html"/>
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287 </outputs>
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288
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289
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290 <help><![CDATA[
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291 .. class:: infomark
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292
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293 The query gene set is limited to n = 200 identifiers. Running with more identifiers can be done through the stand-alone R package. A very limited query gene set (e.g. n < 5) will in general reduce the relevance and significance of many oncoEnrichR report modules (i.e. protein-protein interaction networks, functional enrichment etc.).
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294
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295 -----
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296
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297 **Dataset formats**
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298
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299 The input dataset is in tabular_ format. The two output datasets are html_ and xlsx.
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300
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301 .. _tabular: ${static_path}/formatHelp.html#tab
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302 .. _html: ${static_path}/formatHelp.html#html
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303
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304 -----
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305
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306 **What it does**
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307
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308 *OncoEnrichR* is intended for exploratory analysis and prioritization of a candidate hits (referred to as *query set* below) from high-throughput cancer biology experiments. The tool queries a number of high-quality data resources in order to interpret the query gene set along various dimensions, examples being cancer aberration frequencies, protein-protein interactions, pathway enrichment, subcellular compartment localization, target druggability, gene fitness scores, and regulatory interactions.
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309
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310 The results from the various analysis modules are provided in an interactive HTML report where the user can interrogate the results further. A multisheet Excel workbook is also provided for convience. The following resources are currently utilized for annotation and analysis:
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311
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312 - `Open Targets Platform <https://targetvalidation.org/>`_ - disease associations, drug-target associations, cancer hallmarks, and druggability/tractability rankings
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313
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314 - `The Cancer Genome Atlas <https://portal.gdc.cancer.gov/>`_ - gene aberration frequencies and co-expression patterns in approximately 10,000 primary tumor samples
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315
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316 - `The Human Protein Atlas <https://www.proteinatlas.org/>`_ - expression data for healthy human tissues (`GTex <https://gtexportal.org/home/>`_)/cell types, and prognostic gene expression associations in cancer (`The Pathology Atlas <https://www.proteinatlas.org/humanproteome/pathology/>`_)
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317
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318 - `Molecular Signatures Database (MSigDB) <http://software.broadinstitute.org/gsea/msigdb/index.jsp/>`_ - collection of annotated (e.g. towards pathways) gene sets for enrichment/overrepresentation analysis. This includes gene sets from `Gene Ontology <http://geneontology.org/>`_, `Reactome <https://reactome.org/>`_, `KEGG <https://www.genome.jp/kegg/pathway.html/>`_, `WikiPathways <https://www.wikipathways.org/index.php/WikiPathways/>`_, `BIOCARTA <https://maayanlab.cloud/Harmonizome/dataset/Biocarta+Pathways/>`_, as well as curated `immunologic <https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp#C7/>`_ and `cancer-specific <https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp#C6/>`_ signatures.
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319
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320 - `NetPath <http://www.netpath.org/>`_ - manually curated resource of signal transduction pathways in humans
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321
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322 - `UniProt <https://uniprot.org>`_ - Comprehensive resource of protein sequence and functional information
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323
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324 - `STRING <https://string-db.org/>`_ - protein-protein interaction database
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325
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326 - `InterPro/PFAM <https://www.ebi.ac.uk/interpro/>`_ - Collection of protein families/domains`
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327
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328 - `BIOGRID <http://thebiogrid.org>`_ - Database of Protein, Genetic and Chemical Interactions
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329
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330 - `CellChatDB <http://www.cellchat.org/>`_ - database on ligand-receptor interactions
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331
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332 - `DoRothEA <https://saezlab.github.io/dorothea/>`_ - gene set resource containing signed transcription factor (TF) - target interactions
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333
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334 - `CORUM <https://mips.helmholtz-muenchen.de/corum/>`_ - protein complex database
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335
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336 - `Compleat <https://fgr.hms.harvard.edu/compleat>`_ - protein complex resource
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337
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338 - `ComplexPortal <https://www.ebi.ac.uk/complexportal/home/>`_ - manually curated, encyclopaedic resource of macromolecular complexes
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339
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340 - `hu.MAP2 <http://humap2.proteincomplexes.org/>`_ - human protein complex map
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341
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342 - `COMPARTMENTS <https://compartments.jensenlab.org/Search/>`_ - subcellular compartment annotation database
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343
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344 - `CancerMine <http://bionlp.bcgsc.ca/cancermine/>`_ - literature-mined resource on cancer drivers, oncogenes and tumor suppressor genes
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345
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346 - `Cancer Gene Census <https://cancer.sanger.ac.uk/census/>`_ - Curated high-confidence list of genes with substantial published evidence in oncology
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347
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348 - `Network of Cancer Genes <http://ncg.kcl.ac.uk/>`_ - manually curated collection of cancer genes, healthy drivers and their properties
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349
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350 - `DepMap/Project Score <https://score.depmap.sanger.ac.uk/>`_ - database on the effects on cancer cell line viability elicited by CRISPR-Cas9 mediated gene activation
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351
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352 - `Genetic determinants of survival in cancer <http://survival.cshl.edu/>`_ - resource on the prognostic impact of genetic aberrations (methylation, CNA, mutation, expression) in human cancers (TCGA)
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353
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354 - `Predicted synthetic lethality interactions <https://pubmed.ncbi.nlm.nih.gov/34529928/>`_ - comprehensive prediction of synthetic lethality interactions in human cancer cell lines
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355
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356 The contents of the gene set analysis report attempt to answer the following questions related to the query set:
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357
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358 - Which diseases/tumor types are known to be associated with genes in the query set, and to what extent? Which genes show evidence of oncogenic and/or tumor suppressive roles?
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359
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360 - Which query genes have been linked (through literature) to the various hallmarks of cancer?
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361
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362 - Which genes in the query set are poorly characterized or have an unknown function?
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363
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364 - Which proteins in the query set can be targeted by inhibitors for diffferent cancer conditions (early and late clinical development phases)? What is the tractability/druggability status for other targets in the query set?
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365
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366 - Which cancer-relevant protein complexes are involved for proteins in the query set?
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367
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368 - Are there known cancer-relevant regulatory interactions (transcription factor (TF) - target) found in the query set?
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369
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370 - Are there known ligand-receptor interactions in the query set?
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371
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372 - Which subcellular compartments (nucleus, cytosol, plasma membrane etc.) are dominant localizations for members of the query set?
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373
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374 - Which protein-protein interactions are known within the query set? Are there interactions between members of the query set and other cancer-relevant proteins (e.g. proto-oncogenes, tumor-suppressors or predicted cancer drivers)? Which proteins constitute hubs in the protein-protein interaction network?
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375
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376 - Are there specific pathways, biological processes or molecular functions that are enriched within the query set, as compared to a reference/background set?
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377
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378 - Which members of the query set are frequently mutated in tumor sample cohorts (TCGA - SNVs/InDels / homozygous deletions / copy number amplifications)? What are the most frequent recurrent somatic variants (SNVs/InDels) in the query set genes?
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379
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380 - Which members of the query set are co-expressed (strong negative or positive correlations) with cancer-relevant genes (i.e. proto-oncogenes or tumor suppressors) in tumor sample cohorts (TCGA)?
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381
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382 - Which members of the query set are associated with better/worse survival in different cancers, considering mutation, expression, methylation or copy number levels in tumors?
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383
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384 - Which members of the query set are predicted as partners of synthetic lethality interactions?
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385
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386 - Which members of the query set are associated with cellular loss-of-fitness in CRISPR/Cas9 whole-genome drop out screens of cancer cell lines (i.e. reduction of cell viability elicited by a gene inactivation)? Which genes should be prioritized considering genomic biomarkers and fitness scores in combination?
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387
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388
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389 ]]>
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390 </help>
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391
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392 <citations>
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393 <!-- Example of annotating a citation using a DOI. -->
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394 <citation type="doi">10.1002/ijc.34666</citation>
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395 <!-- Example of annotating a citation using a BibTex entry. -->
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396 </citations>
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397 </tool>
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