Difference between revisions of "Uproc"
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| − | [[Category:Software]][[Category: | + | [[Category:Software]][[Category:Genomics]][[Category:Biology]] |
{|<!--CONFIGURATION: REQUIRED--> | {|<!--CONFIGURATION: REQUIRED--> | ||
|{{#vardefine:app|uproc}} | |{{#vardefine:app|uproc}} | ||
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|{{#vardefine:conf|}} <!--CONFIGURATION--> | |{{#vardefine:conf|}} <!--CONFIGURATION--> | ||
| − | |{{#vardefine:exe|}} <!--ADDITIONAL INFO--> | + | |{{#vardefine:exe|1}} <!--ADDITIONAL INFO--> |
| − | |{{#vardefine: | + | |{{#vardefine:pbs|}} <!--PBS SCRIPTS--> |
|{{#vardefine:policy|}} <!--POLICY--> | |{{#vardefine:policy|}} <!--POLICY--> | ||
|{{#vardefine:testing|}} <!--PROFILING--> | |{{#vardefine:testing|}} <!--PROFILING--> | ||
|{{#vardefine:faq|}} <!--FAQ--> | |{{#vardefine:faq|}} <!--FAQ--> | ||
| − | |{{#vardefine:citation|}} <!--CITATION--> | + | |{{#vardefine:citation|1}} <!--CITATION--> |
|{{#vardefine:installation|}} <!--INSTALLATION--> | |{{#vardefine:installation|}} <!--INSTALLATION--> | ||
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{{App_Description|app={{#var:app}}|url={{#var:url}}|name={{#var:app}}}}|}} | {{App_Description|app={{#var:app}}|url={{#var:url}}|name={{#var:app}}}}|}} | ||
| − | With rapidly increasing volumes of biological sequence data the functional analysis of new sequences in terms of similarities to known protein families challenges classical bioinformatics. The ultrafast protein classification (UProC) toolbox implements a novel algorithm ("Mosaic Matching") for large-scale sequence analysis and is now available in terms of an open source C library. UProC is up to three orders of magnitude faster than profile-based methods and achieved up to 80% higher sensitivity on unassembled short reads (100 bp) from simulated metagenomes. UProC does not depend on a multiple alignment of family-specific sequences. Therefore, in addition to the protein domain classfication according to the Pfam database, UProC can, in principle, also provide the detection of KEGG Orthologs. We provide a precompiled database for KEGG Ortholog classification | + | With rapidly increasing volumes of biological sequence data the functional analysis of new sequences in terms of similarities to known protein families challenges classical bioinformatics. The ultrafast protein classification (UProC) toolbox implements a novel algorithm ("Mosaic Matching") for large-scale sequence analysis and is now available in terms of an open source C library. UProC is up to three orders of magnitude faster than profile-based methods and achieved up to 80% higher sensitivity on unassembled short reads (100 bp) from simulated metagenomes. UProC does not depend on a multiple alignment of family-specific sequences. Therefore, in addition to the protein domain classfication according to the Pfam database, UProC can, in principle, also provide the detection of KEGG Orthologs. We provide a precompiled database for KEGG Ortholog classification (see below) but we have not evaluated the classification performance for that database so far. |
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Run <code>module spider {{#var:app}}</code> to find out what environment modules are available for this application. | Run <code>module spider {{#var:app}}</code> to find out what environment modules are available for this application. | ||
==System Variables== | ==System Variables== | ||
| − | * HPC_{{ | + | * HPC_{{uc:{{#var:app}}}}_DIR - installation directory |
| − | * HPC_{{ | + | * HPC_{{uc:{{#var:app}}}}_BIN - executable directory |
| − | * HPC_{{ | + | * HPC_{{uc:{{#var:app}}}}_LIB - library directory |
| − | * HPC_{{ | + | * HPC_{{uc:{{#var:app}}}}_INC - includes directory |
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<!--Configuration--> | <!--Configuration--> | ||
{{#if: {{#var: conf}}|==Configuration== | {{#if: {{#var: conf}}|==Configuration== | ||
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{{#if: {{#var: exe}}|==Additional Information== | {{#if: {{#var: exe}}|==Additional Information== | ||
| − | + | Imported UProC KeGG and PFam databases are located at $DBDR (or $HPC_UPROC_DBDIR) and $MODELDIR (or $HPC_UPROC_MODELDIR), so the above variables can be used on the command-line. | |
|}} | |}} | ||
| − | <!-- | + | <!--PBS scripts--> |
| − | {{#if: {{#var: | + | {{#if: {{#var: pbs}}|==PBS Script Examples== |
| − | See the [[{{PAGENAME}} | + | See the [[{{PAGENAME}}_PBS]] page for {{#var: app}} PBS script examples. |
|}} | |}} | ||
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If you publish research that uses {{#var:app}} you have to cite it as follows: | If you publish research that uses {{#var:app}} you have to cite it as follows: | ||
| − | + | Meinicke, Peter. '''UProC: tools for ultra-fast protein domain classification'''. ''Bioinformatics'', 2014 | |
|}} | |}} | ||
Latest revision as of 20:53, 12 August 2022
Description
With rapidly increasing volumes of biological sequence data the functional analysis of new sequences in terms of similarities to known protein families challenges classical bioinformatics. The ultrafast protein classification (UProC) toolbox implements a novel algorithm ("Mosaic Matching") for large-scale sequence analysis and is now available in terms of an open source C library. UProC is up to three orders of magnitude faster than profile-based methods and achieved up to 80% higher sensitivity on unassembled short reads (100 bp) from simulated metagenomes. UProC does not depend on a multiple alignment of family-specific sequences. Therefore, in addition to the protein domain classfication according to the Pfam database, UProC can, in principle, also provide the detection of KEGG Orthologs. We provide a precompiled database for KEGG Ortholog classification (see below) but we have not evaluated the classification performance for that database so far.
Environment Modules
Run module spider uproc to find out what environment modules are available for this application.
System Variables
- HPC_UPROC_DIR - installation directory
- HPC_UPROC_BIN - executable directory
- HPC_UPROC_LIB - library directory
- HPC_UPROC_INC - includes directory
Additional Information
Imported UProC KeGG and PFam databases are located at $DBDR (or $HPC_UPROC_DBDIR) and $MODELDIR (or $HPC_UPROC_MODELDIR), so the above variables can be used on the command-line.
Citation
If you publish research that uses uproc you have to cite it as follows:
Meinicke, Peter. UProC: tools for ultra-fast protein domain classification. Bioinformatics, 2014