Mercurial > repos > bjoern-gruening > iprscan
comparison interproscan.xml @ 1:94745fda6aff draft
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author | bjoern-gruening |
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date | Sun, 23 Jun 2013 07:38:53 -0400 |
parents | 341830c8cd37 |
children | 99517734aa65 |
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0:341830c8cd37 | 1:94745fda6aff |
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1 <tool id="interproscan" name="Interproscan functional predictions of ORFs" version="1.1"> | 1 <tool id="interproscan" name="Interproscan functional predictions of ORFs" version="1.2"> |
2 <description>Interproscan functional predictions of ORFs</description> | 2 <description>Interproscan functional predictions of ORFs</description> |
3 <command> | 3 <command> |
4 ## The command is a Cheetah template which allows some Python based syntax. | 4 ## The command is a Cheetah template which allows some Python based syntax. |
5 ## Lines starting hash hash are comments. Galaxy will turn newlines into spaces | 5 ## Lines starting hash hash are comments. Galaxy will turn newlines into spaces |
6 | 6 |
7 ## create temp directory | 7 ## create temp directory |
9 #set $tfile = tempfile.mkstemp()[1] | 9 #set $tfile = tempfile.mkstemp()[1] |
10 | 10 |
11 sed 's/ /_/g' $input > $tfile; | 11 sed 's/ /_/g' $input > $tfile; |
12 | 12 |
13 ## Hack, because interproscan does not seem to produce gff output even if it is configured | 13 ## Hack, because interproscan does not seem to produce gff output even if it is configured |
14 #if str($oformat)=="gff": | 14 #if str($oformat) == "gff": |
15 #set $tfile2 = tempfile.mkstemp()[1] | 15 #set $tfile2 = tempfile.mkstemp()[1] |
16 iprscan -cli -nocrc -i $tfile -o $tfile2 -goterms -seqtype p -altjobs -format raw -appl $appl > /dev/null 2> /dev/null; | 16 iprscan -cli -nocrc -i $tfile -o $tfile2 -goterms -seqtype p -altjobs -format raw -appl $appl 2>&1; |
17 converter.pl -format gff3 -input $tfile2 -output $output | 17 converter.pl -format gff3 -input $tfile2 -output $output; |
18 rm $tfile2 | 18 rm $tfile2; |
19 #else | 19 #else |
20 iprscan -cli -nocrc -i $tfile -o $output -goterms -seqtype p -altjobs -format $oformat -appl $appl > /dev/null 2> /dev/null; | 20 iprscan -cli -nocrc -i $tfile -o $output -goterms -seqtype p -altjobs -format $oformat -appl $appl 2>&1; |
21 #end if | 21 #end if |
22 | 22 |
23 rm $tfile; | 23 rm $tfile |
24 | 24 |
25 </command> | 25 </command> |
26 <inputs> | 26 <inputs> |
27 <param name="input" type="data" format="fasta" label="Protein Fasta File"/> | 27 <param name="input" type="data" format="fasta" label="Protein Fasta File"/> |
28 | 28 |
29 <param name="appl" type="select" format="text" help="Select your programm."> | 29 <param name="appl" type="select" format="text" label="Applications to run" help="Select your programm."> |
30 <label>Applications to run ...</label> | |
31 <option value="blastprodom+coils+gene3d+hamap+hmmpanther+hmmpir+hmmpfam+hmmsmart+hmmtigr+fprintscan+patternscan+profilescan+superfamily+seg+signalp+tmhmm" selected="true">all</option> | 30 <option value="blastprodom+coils+gene3d+hamap+hmmpanther+hmmpir+hmmpfam+hmmsmart+hmmtigr+fprintscan+patternscan+profilescan+superfamily+seg+signalp+tmhmm" selected="true">all</option> |
32 <option value="seg">seg</option> | 31 <option value="seg">seg</option> |
33 <option value="signalp">signalp</option> | 32 <option value="signalp">signalp</option> |
34 <option value="tmhmm">tmhmm</option> | 33 <option value="tmhmm">tmhmm</option> |
35 <option value="fprintscan">fprintscan</option> | 34 <option value="fprintscan">fprintscan</option> |
43 <option value="hmmpanther">hmmpanther</option> | 42 <option value="hmmpanther">hmmpanther</option> |
44 <option value="hamap">hamap</option> | 43 <option value="hamap">hamap</option> |
45 <option value="gene3d">gene3d</option> | 44 <option value="gene3d">gene3d</option> |
46 <option value="coils">coils</option> | 45 <option value="coils">coils</option> |
47 <option value="blastprodom">blastprodom</option> | 46 <option value="blastprodom">blastprodom</option> |
48 </param> | 47 </param> |
49 | 48 |
50 <param name="oformat" type="select" label="Output format" help="Please select a output format."> | 49 <param name="oformat" type="select" label="Output format" help="Please select a output format."> |
51 <option value="gff" selected="true">gff</option> | 50 <option value="gff">gff</option> |
52 <option value="raw">raw</option> | 51 <option value="raw" selected="true">raw</option> |
53 <option value="txt">txt</option> | 52 <option value="txt">txt</option> |
54 <option value="html">html</option> | 53 <option value="html">html</option> |
55 <option value="xml">xml</option> | 54 <option value="xml">xml</option> |
56 <option value="ebixml">EBI header on top of xml</option> | 55 <option value="ebixml">EBI header on top of xml</option> |
57 </param> | 56 </param> |
70 | 69 |
71 </outputs> | 70 </outputs> |
72 <requirements> | 71 <requirements> |
73 </requirements> | 72 </requirements> |
74 <help> | 73 <help> |
75 | |
76 **What it does** | 74 **What it does** |
77 | |
78 | 75 |
79 Interproscan is a batch tool to query the Interpro database. It provides annotations based on multiple searches of profile and other functional databases. | 76 Interproscan is a batch tool to query the Interpro database. It provides annotations based on multiple searches of profile and other functional databases. |
80 These include SCOP, CATH, PFAM and SUPERFAMILY. | 77 These include SCOP, CATH, PFAM and SUPERFAMILY. |
81 | 78 |
82 **Input** | 79 **Input** |
83 A FASTA file containing ORF predictions is required. This file must NOT contain any spaces in the FASTA headers - any spaces will be convereted to underscores (_) by this tool before submission to Interproscan. | 80 |
81 Required is a FASTA file containing ORF predictions. This file must NOT contain any spaces in the FASTA headers - any spaces will be convereted to underscores ``_`` by this tool before running with Interproscan. | |
84 | 82 |
85 **Output** | 83 **Output** |
86 | 84 |
87 Example for the raw format. | 85 Example for the raw format. |
88 This is a basic tab delimited format useful for uploading the data into a relational database or concatenation of different runs. | 86 The output will consist of a tabular file in galaxy with 14 columns and can be easily concatenated or filtered. |
89 is all on one line. | |
90 | 87 |
91 ====== ================================================================ ====================================================================== | 88 ====== ================================================================ ====================================================================== |
92 column example description | 89 column example description |
93 ====== ================================================================ ====================================================================== | 90 ====== ================================================================ ====================================================================== |
94 c1 NF00181542 the id of the input sequence. | 91 c1 NF00181542 the id of the input sequence |
95 c2 27A9BBAC0587AB84 the crc64 (checksum) of the protein sequence (supposed to be unique). | 92 c2 27A9BBAC0587AB84 the crc64 (checksum) of the protein sequence (supposed to be unique) |
96 c3 272 the length of the sequence (in AA). | 93 c3 272 the length of the sequence (in AA) |
97 c4 HMMPIR the anaysis method launched. | 94 c4 HMMPIR the anaysis method launched. |
98 c5 PIRSF001424 the database members entry for this match. | 95 c5 PIRSF001424 the database members entry for this match |
99 c6 Prephenate dehydratase the database member description for the entry. | 96 c6 Prephenate dehydratase the database member description for the entry |
100 c7 1 the start of the domain match. | 97 c7 1 the start of the domain match |
101 c8 270 the end of the domain match. | 98 c8 270 the end of the domain match |
102 c9 6.5e-141 the evalue of the match (reported by member database method). | 99 c9 6.5e-141 the evalue of the match (reported by member database method) |
103 c10 T the status of the match (T: true, ?: unknown). | 100 c10 T the status of the match (T: true, ?: unknown) |
104 c11 06-Aug-2005 the date of the run. | 101 c11 06-Aug-2005 the date of the run. |
105 c12 IPR008237 the corresponding InterPro entry (if iprlookup requested by the user). | 102 c12 IPR008237 the corresponding InterPro entry (if iprlookup requested by the user) |
106 c13 Prephenate dehydratase with ACT region the description of the InterPro entry. | 103 c13 Prephenate dehydratase with ACT region the description of the InterPro entry |
107 c14 Molecular Function:prephenate dehydratase activity (GO:0004664) the GO (gene ontology) description for the InterPro entry. | 104 c14 Molecular Function:prephenate dehydratase activity (GO:0004664) the GO (gene ontology) description for the InterPro entry |
108 ====== ================================================================ ====================================================================== | 105 ====== ================================================================ ====================================================================== |
109 | 106 |
110 | |
111 **Database updates** | 107 **Database updates** |
112 | 108 |
113 Typically these take place 2-3 times a year. | 109 Typically these take place 2-3 times a year. Please contact your Galaxy administrator to update the databases. |
114 | 110 |
115 | 111 ----- |
116 **Tools** | 112 Tools |
117 | 113 ----- |
118 PROSITE patterns | 114 |
119 | 115 **PROSITE patterns**:: |
120 :: | |
121 | 116 |
122 Some biologically significant amino acid patterns can be summarised in | 117 Some biologically significant amino acid patterns can be summarised in |
123 the form of regular expressions. | 118 the form of regular expressions. |
124 ScanRegExp (by Wolfgang.Fleischmann@ebi.ac.uk), | 119 ScanRegExp (by Wolfgang.Fleischmann@ebi.ac.uk). |
125 | 120 |
126 PROSITE profiles | 121 **PROSITE profiles**:: |
127 | |
128 :: | |
129 | 122 |
130 There are a number of protein families as well as functional or | 123 There are a number of protein families as well as functional or |
131 structural domains that cannot be detected using patterns due to their extreme | 124 structural domains that cannot be detected using patterns due to their extreme |
132 sequence divergence, so the use of techniques based on weight matrices | 125 sequence divergence, so the use of techniques based on weight matrices |
133 (also known as profiles) allows the detection of such proteins or domains. | 126 (also known as profiles) allows the detection of such proteins or domains. |
134 A profile is a table of position-specific amino acid weights and gap costs. | 127 A profile is a table of position-specific amino acid weights and gap costs. |
135 The profile structure used in PROSITE is similar to but slightly more general | 128 The profile structure used in PROSITE is similar to but slightly more general |
136 (Bucher P. et al., 1996 [7]) than the one introduced by M. Gribskov and | 129 (Bucher P. et al., 1996) than the one introduced by M. Gribskov and |
137 co-workers. | 130 co-workers. |
138 pfscan from the Pftools package (by Philipp.Bucher@isrec.unil.ch). | 131 pfscan from the Pftools package (by Philipp.Bucher@isrec.unil.ch). |
139 | 132 |
140 PRINTS | 133 **PRINTS**:: |
141 | |
142 :: | |
143 | 134 |
144 The PRINTS database houses a collection of protein family fingerprints. | 135 The PRINTS database houses a collection of protein family fingerprints. |
145 These are groups of motifs that together are diagnostically more | 136 These are groups of motifs that together are diagnostically more |
146 powerful than single motifs by making use of the biological context inherent in a | 137 powerful than single motifs by making use of the biological context inherent in a |
147 multiple-motif method. The fingerprinting method arose from the need for | 138 multiple-motif method. The fingerprinting method arose from the need for |
148 a reliable technique for detecting members of large, highly divergent | 139 a reliable technique for detecting members of large, highly divergent |
149 protein super-families. | 140 protein super-families. |
150 FingerPRINTScan (Scordis P. et al., 1999 [8]). | 141 FingerPRINTScan (Scordis P. et al., 1999). |
151 | 142 |
152 PFAM | 143 **PFAM**:: |
153 | |
154 :: | |
155 | 144 |
156 Pfam is a database of protein domain families. Pfam contains curated | 145 Pfam is a database of protein domain families. Pfam contains curated |
157 multiple sequence alignments for each family and corresponding hidden | 146 multiple sequence alignments for each family and corresponding hidden |
158 Markov models (HMMs) (Eddy S.R., 1998 [9]). | 147 Markov models (HMMs) (Eddy S.R., 1998). |
159 Profile hidden Markov models are statistical models of the primary | 148 Profile hidden Markov models are statistical models of the primary |
160 structure consensus of a sequence family. The construction and use | 149 structure consensus of a sequence family. The construction and use |
161 of Pfam is tightly tied to the HMMER software package. | 150 of Pfam is tightly tied to the HMMER software package. |
162 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, | 151 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, |
163 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). | 152 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). |
164 | 153 |
165 PRODOM | 154 **PRODOM**:: |
166 | |
167 :: | |
168 | |
169 | 155 |
170 ProDom is a database of protein domain families obtained by automated | 156 ProDom is a database of protein domain families obtained by automated |
171 analysis of the SWISS-PROT and TrEMBL protein sequences. It is useful | 157 analysis of the SWISS-PROT and TrEMBL protein sequences. It is useful |
172 for analysing the domain arrangements of complex protein families and the | 158 for analysing the domain arrangements of complex protein families and the |
173 homology relationships in modular proteins. ProDom families are built by | 159 homology relationships in modular proteins. ProDom families are built by |
174 an automated process based on a recursive use of PSI-BLAST homology | 160 an automated process based on a recursive use of PSI-BLAST homology |
175 searches. | 161 searches. |
176 ProDomBlast3i.pl (by Emmanuel Courcelle emmanuel.courcelle@toulouse.inra.fr | 162 ProDomBlast3i.pl (by Emmanuel Courcelle emmanuel.courcelle@toulouse.inra.fr |
177 and Yoann Beausse beausse@toulouse.inra.fr) | 163 and Yoann Beausse beausse@toulouse.inra.fr) |
178 a wrapper on top of the Blast package (Altschul S.F. et al., 1997 [10]). | 164 a wrapper on top of the Blast package (Altschul S.F. et al., 1997). |
179 | 165 |
180 | 166 **SMART**:: |
181 SMART | |
182 | |
183 :: | |
184 | 167 |
185 SMART (a Simple Modular Architecture Research Tool) allows the | 168 SMART (a Simple Modular Architecture Research Tool) allows the |
186 identification and annotation of genetically mobile domains and the | 169 identification and annotation of genetically mobile domains and the |
187 analysis of domain architectures. These domains are extensively | 170 analysis of domain architectures. These domains are extensively |
188 annotated with respect to phyletic distributions, functional class, tertiary | 171 annotated with respect to phyletic distributions, functional class, tertiary |
189 structures and functionally important residues. SMART alignments are | 172 structures and functionally important residues. SMART alignments are |
190 optimised manually and following construction of corresponding hidden Markov models (HMMs). | 173 optimised manually and following construction of corresponding hidden Markov models (HMMs). |
191 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, | 174 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, |
192 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). | 175 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). |
193 | 176 |
194 | 177 **TIGRFAMs**:: |
195 TIGRFAMs | |
196 | |
197 :: | |
198 | 178 |
199 TIGRFAMs are a collection of protein families featuring curated multiple | 179 TIGRFAMs are a collection of protein families featuring curated multiple |
200 sequence alignments, Hidden Markov Models (HMMs) and associated | 180 sequence alignments, Hidden Markov Models (HMMs) and associated |
201 information designed to support the automated functional identification | 181 information designed to support the automated functional identification |
202 of proteins by sequence homology. Classification by equivalog family | 182 of proteins by sequence homology. Classification by equivalog family |
205 for automatic assignment of specific functions to proteins from large | 185 for automatic assignment of specific functions to proteins from large |
206 scale genome sequencing projects. | 186 scale genome sequencing projects. |
207 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, | 187 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, |
208 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). | 188 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). |
209 | 189 |
210 PIR SuperFamily | 190 **PIR SuperFamily**:: |
211 | |
212 :: | |
213 | 191 |
214 PIR SuperFamily (PIRSF) is a classification system based on evolutionary | 192 PIR SuperFamily (PIRSF) is a classification system based on evolutionary |
215 relationship of whole proteins. | 193 relationship of whole proteins. |
216 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, | 194 hmmpfam from the HMMER2.3.2 package (by Sean Eddy, |
217 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). | 195 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). |
218 | 196 |
219 SUPERFAMILY | 197 **SUPERFAMILY**:: |
220 | |
221 :: | |
222 | 198 |
223 SUPERFAMILY is a library of profile hidden Markov models that represent | 199 SUPERFAMILY is a library of profile hidden Markov models that represent |
224 all proteins of known structure, based on SCOP. | 200 all proteins of known structure, based on SCOP. |
225 hmmpfam/hmmsearch from the HMMER2.3.2 package (by Sean Eddy, | 201 hmmpfam/hmmsearch from the HMMER2.3.2 package (by Sean Eddy, |
226 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). | 202 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). |
227 Optionally, predictions for coiled-coil, signal peptide cleavage sites | 203 Optionally, predictions for coiled-coil, signal peptide cleavage sites |
228 (SignalP v3) and TM helices (TMHMM v2) are supported (See the FAQs file | 204 (SignalP v3) and TM helices (TMHMM v2) are supported (See the FAQs file |
229 for details). | 205 for details). |
230 | 206 |
231 | 207 **GENE3D**:: |
232 GENE3D | 208 |
233 | 209 Gene3D is supplementary to the CATH database. This protein sequence database |
234 :: | 210 contains proteins from complete genomes which have been clustered into protein |
235 | 211 families and annotated with CATH domains, Pfam domains and functional |
236 Gene3D is supplementary to the CATH database. This protein sequence database | 212 information from KEGG, GO, COG, Affymetrix and STRINGS. |
237 contains proteins from complete genomes which have been clustered into protein | 213 hmmpfam from the HMM2.3.2 package (by Sean Eddy, |
238 families and annotated with CATH domains, Pfam domains and functional | 214 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). |
239 information from KEGG, GO, COG, Affymetrix and STRINGS. | 215 |
240 hmmpfam from the HMM2.3.2 package (by Sean Eddy, | 216 **PANTHER**:: |
241 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). | 217 |
242 | 218 The PANTHER (Protein ANalysis THrough Evolutionary Relationships) |
243 | 219 Classification System was designed to classify proteins (and their genes) |
244 PANTHER | 220 in order to facilitate high-throughput analysis. |
245 | 221 hmmsearch from the HMM2.3.2 package (by Sean Eddy, |
246 :: | 222 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). |
247 | 223 and blastall from the Blast package (Altschul S.F. et al., 1997). |
248 The PANTHER (Protein ANalysis THrough Evolutionary Relationships) | 224 |
249 Classification System was designed to classify proteins (and their genes) | 225 ---------- |
250 in order to facilitate high-throughput analysis. | 226 References |
251 hmmsearch from the HMM2.3.2 package (by Sean Eddy, | 227 ---------- |
252 eddy@genetics.wustl.edu, http://hmmer.wustl.edu). | 228 |
253 and blastall from the Blast package (Altschul S.F. et al., 1997 [10]). | 229 Zdobnov EM, Apweiler R (2001) |
254 | 230 InterProScan an integration platform for the signature-recognition methods in InterPro. |
255 | 231 Bioinformatics 17, 847-848. |
256 | 232 http://dx.doi.org/10.1093/bioinformatics/17.9.847 |
257 **References** | 233 |
258 | 234 Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, Lopez R (2005) |
259 Quevillon E., Silventoinen V., Pillai S., Harte N., Mulder N., Apweiler R., Lopez R. | 235 InterProScan: protein domains identifier. |
260 InterProScan: protein domains identifier (2005). | 236 Nucleic Acids Research 33 (Web Server issue), W116-W120. |
261 Nucleic Acids Res. 33 (Web Server issue) :W116-W120 | 237 http://dx.doi.org/10.1093/nar/gki442 |
262 | 238 |
263 Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, Selengut JD, Sigrist CJ, Thimma M, Thomas PD, Valentin F, Wilson D, Wu CH, Yeats C. | 239 Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, Selengut JD, Sigrist CJ, Thimma M, Thomas PD, Valentin F, Wilson D, Wu CH, Yeats C. (2009) |
264 InterPro: the integrative protein signature database (2009). | 240 InterPro: the integrative protein signature database. |
265 Nucleic Acids Res. 37 (Database Issue) :D224-228 | 241 Nucleic Acids Research 37 (Database Issue), D224-228. |
266 | 242 http://dx.doi.org/10.1093/nar/gkn785 |
267 Galaxy Wrapper Author: | 243 |
268 | 244 |
269 * Bjoern Gruening, Pharmaceutical Bioinformatics, University of Freiburg | 245 **Galaxy Wrapper Author**:: |
270 * Konrad Paszkiewicz, Exeter Sequencing Service, University of Exeter | 246 |
271 | 247 * Bjoern Gruening, Pharmaceutical Bioinformatics, University of Freiburg |
272 | 248 * Konrad Paszkiewicz, Exeter Sequencing Service, University of Exeter |
273 | 249 |
274 </help> | 250 </help> |
275 </tool> | 251 </tool> |