comparison GO_terms_enrich_comparison.xml @ 1:528652235016 draft

planemo upload commit c9d70181a2b587e53dcc4b5885b74b625def6b8c-dirty
author proteore
date Fri, 13 Dec 2019 05:16:36 -0500
parents 04f363ee805a
children ec6f7de49e86
comparison
equal deleted inserted replaced
0:04f363ee805a 1:528652235016
1 <tool id="go_terms_enrich_comparison" name="GO terms enrich comparison " version="2019.11.19.1"> 1 <tool id="go_terms_enrich_comparison" name="GO terms enrich comparison " version="2019.12.13">
2 <description>(Human, Mouse, Rat)[clusterProfiler]</description> 2 <description>(Human, Mouse, Rat)[clusterProfiler]</description>
3 <requirements> 3 <requirements>
4 <requirement type="package">R</requirement> 4 <requirement type="package">R</requirement>
5 <requirement type="package" version="3.8.2">bioconductor-org.hs.eg.db</requirement> 5 <requirement type="package" version="3.8.2">bioconductor-org.hs.eg.db</requirement>
6 <requirement type="package" version="3.8.2">bioconductor-org.mm.eg.db</requirement> 6 <requirement type="package" version="3.8.2">bioconductor-org.mm.eg.db</requirement>
133 </tests> 133 </tests>
134 <help><![CDATA[ 134 <help><![CDATA[
135 135
136 **Description** 136 **Description**
137 137
138 This tool is based on R package clusterProfiler and allows to perform GO terms classification and enrichment analyses on gene/protein sets (e.g. given a set of genes that are up-regulated under certain conditions, an enrichment analysis will find which GO terms are over-represented (or under-represented) using annotations for that gene/protein set). 138 This tool is based on the R package clusterProfiler and allows to compare GO terms enrichment analyses of gene/protein sets.
139 139 Given a list of gene set, this function will compute GO enrichment profiles of each gene list.
140 Given a list of IDs, this tool: 140
141 141 This tool calculates GO categories enrichment (over- or under-representation) for the IDs of the input list, compared to a background.
142 (i) performs gene classification based on GO distribution at a specific level, 142 User has the possibility to use background corresponding to the whole organism or to a user-defined list.
143 143 In this latter case, user has the possibility to use the "Build tissue-specific expression dataset" ProteoRE tool to create this list according to your need.
144 (ii) calculates GO categories enrichment (over- or under-representation) for the IDs of the input list, compared to a background. User has the possibility to use background corresponding to the whole organism or to a user-defined list. In this latter case, we recommand to use the "Build tissue-specific expression dataset" ProteoRE tool to create this list according to your need.
145 144
146 ----- 145 -----
147 146
148 **Input** 147 **Input**
149 148
150 Two modes are allowed: either by supplying a tabular file (.csv, .tsv, .txt, .tab) including your IDs (identifiers) or by copy/pasting your IDs (separated by a space). 149 Two modes are allowed: either by supplying a tabular file (.csv, .tsv, .txt, .tab) including your IDs (identifiers) or by copy/pasting your IDs (separated by a space).
151 150
152 "Select type/source of IDs": only entrez gene ID (e.g : 4151, 7412) or Uniprot accession number (e.g. P31946) are allowed. If your list is not in this form, please use the ID_Converter tool of ProteoRE. 151 "Enter your Gene ID list": only Entrez Gene ID (e.g : 4151, 7412).
152 If your IDs are not Entrez Gene IDs, please use the ID_Converter tool of ProteoRE.
153
154 "Does file contain header?": in case of file input, you specify if there is header or not.
155
156 "Column number of IDs": in which column are your IDs. (e.g. for column 2 you write "c2")
157
158 "name of your list": write the name for this list
153 159
154 ----- 160 -----
155 161
156 **Parameters** 162 **Parameters**
157 163
158 "Species": the three supported species are Homo sapiens, Mus musculus and Rattus norvegicus 164 "Species": the three supported species are Homo sapiens, Mus musculus and Rattus norvegicus
159 165
160 "Perform GO categories representation analysis?": classify genes based on their projection at a specific level of the GO corpus (see parameter below), and provides functions (set to "Yes") 166 "Select GO terms category": allows you to perform analysis on one, two or three categories of the Gene Ontology. The categories are
161 167 Cellular Component (CC), Biological Process (BP) and Molecular Function (MF).
162 "Ontology level (the higher this number, the deeper the GO level)": correspond to the level of GO hierarchy (from 1 to 3) (set to level "2" by default). In general the higher the level, the more semantically specific the term is.
163
164 "Perform GO categories enrichment analysis?": calculate enrichment test for GO terms based on hypergeometric distribution (set to "Yes")
165
166 "P-value cut off": P-value threshold value for the declaration of significance (default is < 0.01)
167
168 "Q-value cut off": to prevent high false discovery rate (FDR) in multiple testing, Q-values (adjusted P-values) are estimated for FDR control. (default is < 0.05)
169
170 "Define your own background IDs?": by default the whole genome/proteome is used as a reference background to compute the enrichment. As this reference set should normally only include genes/proteins that were monitored during your analysis, this option allows to provide your own background; this could be for instance, the total number of genes/proteins expressed in the tissue/sample under study.
171
172 If you want to use your own background, click on the "Yes" button. Your gene/protein set must be a list of Entrez gene ID or Uniprot accession number (otherwise, use the ID-Converter tool of ProteoRE). Select the file containing your list of ID (as background), then specify the column number which contains IDs and the type of IDs (gene Entrez or Uniprot Accession number) as requested.
173
174 Of note: for Human species, you can build your own background by using the "Build tissue-specific expression dataset" tool of ProteoRE.
175 168
176 ----- 169 -----
177 170
178 **Output** 171 **Output**
179 172
180 Diagram output: graphical output in the form of bar-plot or dot-plot (png, jpeg or pdf format), one figure for each GO category. 173 Diagram output: graphical output in the form of a dot-plot (png, jpeg or pdf format), one figure for each GO category.
181 Text tables: with the following information GO category description (e.g.BP.Description), GO term identifier (e.g. BP.GOID) and GO term frequency (e.g. BP.Frequency)d graphics representing the repartition and/or enrichment of GO categories. One table and one graphic will be produced for each GO catagory. 174 Text tables: with the following information GO category description (e.g.BP.Description), GO term identifier (e.g. BP.GOID) and GO term frequency (e.g. BP.Frequency)d graphics representing the repartition and/or enrichment of GO categories. One table and one graphic will be produced for each GO catagory.
182 175
183 ----- 176 -----
184 177
185 **Authors** 178 **Authors**