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[gofriends] Automatic Gene Ontology Annotation Tools

Javier Forment Millet jforment at ibmcp.upv.es
Mon May 21 04:10:24 PDT 2007


Hi,... I would like to do some comments about the suggestion of including
EST2uni in a list of public available tools who are able to generate or predict
automatically gene ontology annotations based on sequence data.

EST2uni (http://www.melogen.upv.es/genomica/web_estpipe/) is an open, parallel
tool for automated EST analysis and annotation, and database creation with a
data mining web interface. It is an integrated, highly-configurable EST
analysis and data mining software package that completely automates the
pre-processing, clustering, annotation, database creation, and data mining of
EST collections. It can be run in parallel in a PC cluster in order to reduce
the time necessary to do the analysis. A web site linked to the database
showing statistics on the collection, with complex queries capabilities, and
tools for data mining and retrieval is also created by EST2uni.

EST2uni includes a step of functional annotation of the unigenes using Gene
Ontology classification, but, at the moment, it uses a simple BLAST comparison
with a GO-annotated organism, taking the GO annotation of the top-BLAST hit.
However, the EST2uni pipeline uses standard EST analysis tools and the software
has a modular design to ease the addition of new analysis and the configuration
of the existing ones, so it is easy to include any GO-annotation tool which
could be used automatically in a computer pipeline. Actually, we are in the
process of including BLAST2GO as a GO-annotation tool in EST2uni.

Regarding this, it could be very interesting to add this feature to the table of
features of the GO annotation tools that you are preparing, i.e, the ability to
integrate the GO annotation tool in an automated pipeline (not only available
as an stand-alone application). We think that it is a very important and
desirable feature in order to be able to integrate the GO annotation tool with
other analysis tools.

Thanks, and keep on the good work...

Javier.



Mensaje citado por Stefan Goetz <sgoetz at cipf.es>:

> Hi All,
> we are trying to make an up-to-date list of all the working, free and
> public available tools who are able to generate or predict automatically
> (not only  recover) gene ontology annotations based on (novel) sequence
> data. We made a first listing and would like to invite you all to
> discuss, complete or correct this list. Thanks in advanced for your
> contributions and help.
> Regards,
> Stefan Goetz
>
>
> Automatic Gene Ontology Annotation Tools
> (alphabetical order)
>
> NR: 1
> Name: AutoFact
> Paper: BMC BioInformatics, 2005
> High-throughput: yes
> Input Data: fasta
> Method: sequences are classified into 6 different annotation categories,
> blast-based
> Evidence Codes: no
> Manual GO curation: GO, COG, KEGG, Locus, ?
> GO tree visualisation: no
> GO graph visualisation: no
> Avalible: Perl implementation online
> Description: An Automatic Functional Annotation and Classification Tool
> Link: http://www.bch.umontreal.ca/Software/AutoFACT.htm
>
> NR: 2
> Name: Blast2GO
> Paper: Bioinformatics. 2005 Sep
> High-throughput: yes (arround 30 000 Seqs, memory dependent)
> Input Data: fasta, blast-xml
> Method: combination of similarity search based (blast), domain based
> (interproscan) and datamining based (annex) annotation
> Annotation types: GO, InterPro, Kegg
> Evidence Codes: yes
> Manual GO curation: yes
> GO tree visualisation: no
> GO graph visualisation: yes
> Avalible: java web start + web service
> Description: A universal Gene Ontology annotation, visualization and
> analysis tool for functional genomics research
> Link: http://www.blast2go.org
>
> NR: 3
> Name: GOanna/AgBase
> Paper: BMC Genomics
> High-throughput: file upload (size limit?), (user gets notified by email
> when data is ready)
> Input Data: fasta
> Method: Top-Blast
> Annotation types: GO, ?
> Evidence Codes: yes
> Manual GO curation: no
> GO tree visualisation: -
> GO graph visualisation: -
> Avalible: webinterface
> Description: GOanna is used to find annotations for proteins using
> similarity search. The resulting file contains GO annotations of the top
> BLAST hits. The sequence alignments are also provided so the user can
> use these to access the quality of the match.
> Link: http://agbase.msstate.edu/GOAnna.html
>
> NR: 4
> Name: GOAnno
> Paper: Bioinformatics. 2005 May
> High-throughput: one at a time
> Input Data: only proteins, fasta
> Method: evolutionary information in multible alignments organized
> herarchically into functional subfamilies
> Annotation types: GO, ?
> Evidence Codes: no
> Manual GO curation: no
> GO tree visualisation: -
> GO graph visualisation: -
> Avalible: webinterface
> Description: GO annotation based on multiple alignment
> Link: http://bips.u-strasbg.fr/GOAnno/
>
> NR: 5
> Name: GOblet
> Paper: Two NAR papers, 2003,2004
> High-throughput: max ~150 seqs
> Input Data: fasta
> Method: all-hits mapping with probability scoring
> Annotation types: GO
> Evidence Codes: no
> Manual GO curation: no
> GO tree visualisation: yes
> GO graph visualisation: no
> Avalible: webinterface, output in java applet
> Description: A platform for Gene Ontology annotation of anonymous
> sequence data
> Link: http://goblet.molgen.mpg.de
>
> NR: 6
> Name:GoFigure + GoDel
> Paper: Bioinformatics. 2003 Dec
> High-throughput: one at a time
> Input Data: fasta
> Method: GoFigure (mappping of GO terms to Blast Hits) + GODel (Selection
> of terms by eValue and evicdence codes)
> Annotation types: GO
> Evidence Codes: yes
> Manual GO curation: no
> GO tree visualisation: no
> GO graph visualisation: yes
> Avalible: webinterface
> Description: BLAST to predict Gene Ontology annotation
> Link: http://udgenome.ags.udel.edu/gofigure/
>
> NR: 7
> Name: GOtcha
> Paper: no publication
> High-throughput: one at a time
> Input Data: fasta?
> Method: all-hits mapping with probability scoring
> Annotation types: GO
> Evidence Codes: yes
> Manual GO curation: no
> GO tree visualisation: yes
> GO graph visualisation: no
> Avalible: webinterface
> Description: GOtcha uses sequence similarity searches to associate GO
> terms with your sequence. These are ranked by probability and displayed
> graphically on a subtree of Gene Ontology. You will need an up to date
> browser and JavaScript to get the best from the results.
> Link: http://www.compbio.dundee.ac.uk/gotcha/gotcha.php
>
> NR: 8
> Name: HT-GO-FAT
> Paper: no publication
> High-throughput: yes
> Input Data: -
> Method: sequence similarity (custom blast db)
> Annotation types: GO, ?
> Evidence Codes: no
> Manual GO curation: ?
> GO tree visualisation: ?
> GO graph visualisation: ?
> Avalible: Windows .NET (download after request)
> Description: High Throughput Gene Ontology Functional Annotation Toolkit
> (Ht-Go-Fat) Utilized for Animal and Plant
> Link: http://genome4.ars.usda.gov/farm/dload.php
>
> NR: 9
> Name: InterProScan
> Paper: Nucleic Acids Res. 2007
> High-throughput:  max. 10 Seqs (web interface)
> Input Data: fasta
> Method: GOs through domains
> Annotation types: GO, ?
> Evidence Codes: no
> Manual GO curation: no
> GO tree visualisation: no
> GO graph visualisation: no
> Avalible: webinterface, web service
> Description: Domain searches agains: BlastProDom, FPrintScan, HMMPIR,
> HMMPfam, HMMSmart, HMMTigr, ProfileScan, ScanRegExp, SuperFamily,
> SignalPHMM, TMHMM, HMMPanther, Gene3D
> Link: http://www.ebi.ac.uk/InterProScan/
>
> NR: 10
> Name: JAFA
> Paper: no publication
> High-throughput: one at a time
> Input Data: only proteins, fasta
> Method: Joined Assembly of Function Annotations (InterProScan,
> GOtcha,GoFigure, Goblet, Phydbac)
> Annotation types: GO
> Evidence Codes: yes/no
> Manual GO curation: no
> GO tree visualisation: no
> GO graph visualisation: no
> Avalible: webinterface
> Description: Joined Assembly of Function Annotations (InterProScan,
> GOtcha, GoFigure, Goblet, Phydbac)
> Link: http://jafa.burnham.org
>
> NR: 11
> Name: OntoBlast
> Paper: Nucleic Acids Res. 2003
> High-throughput: one at a time
> Input Data: only protein, fasta
> Method: sequence similarities
> Annotation types: GO
> Evidence Codes: no
> Manual GO curation: no
> GO tree visualisation: no
> GO graph visualisation: no
> Avalible: webinterface
> Description: OntoBlast function: From sequence similarities directly to
> potential functional annotations by ontology terms
> Link: http://functionalgenomics.de/ontogate/
>
>
> NR: 12
> CompuGen?
>
> NR: 13
> GOA?
>
> NR: 13
> GOAT?
>
> NR: 14
> est2uni?
>
>
> ...
>
>
>
> --
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-- 
Javier Forment Millet
Instituto de Biología Celular y Molecular de Plantas (IBMCP) CSIC-UPV
 Ciudad Politécnica de la Innovación (CPI) Edificio 8 E, Escalera 7 Puerta E
 Calle Ing. Fausto Elio s/n. 46022 Valencia, Spain
Tlf.:+34-96-3877858
FAX: +34-96-3877859
jforment at ibmcp.upv.es



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