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GRYFUN: a web application for GO term annotation visualization and analysis in protein sets.

Bastos HP, Sousa L, Clarke LA, Couto FM - PLoS ONE (2015)

Bottom Line: This in turn can introduce issues regarding the interpretation of actual functional similarity and overall functional coherence of such a group.One way to mitigate such issues is through the use of visualization and statistical techniques.Therefore, in order to help interpret this annotation heterogeneity we created a web application that generates Gene Ontology annotation graphs for protein sets and their associated statistics from simple frequencies to enrichment values and Information Content based metrics.

View Article: PubMed Central - PubMed

Affiliation: LaSIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.

ABSTRACT
Functional context for biological sequence is provided in the form of annotations. However, within a group of similar sequences there can be annotation heterogeneity in terms of coverage and specificity. This in turn can introduce issues regarding the interpretation of actual functional similarity and overall functional coherence of such a group. One way to mitigate such issues is through the use of visualization and statistical techniques. Therefore, in order to help interpret this annotation heterogeneity we created a web application that generates Gene Ontology annotation graphs for protein sets and their associated statistics from simple frequencies to enrichment values and Information Content based metrics. The publicly accessible website http://xldb.di.fc.ul.pt/gryfun/ currently accepts lists of UniProt accession numbers in order to create user-defined protein sets for subsequent annotation visualization and statistical assessment. GRYFUN is a freely available web application that allows GO annotation visualization of protein sets and which can be used for annotation coherence and cohesiveness analysis and annotation extension assessments within under-annotated protein sets.

No MeSH data available.


PL1 Set non-IEA annotation graph for the GO molecular function sub-ontology.Annotation graph subsuming the PL1 (within the CAZy Collection) Set GO molecular function sub-ontology annotations without electronic annotations (IEA).
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pone.0119631.g007: PL1 Set non-IEA annotation graph for the GO molecular function sub-ontology.Annotation graph subsuming the PL1 (within the CAZy Collection) Set GO molecular function sub-ontology annotations without electronic annotations (IEA).

Mentions: In addition, we used the Evidence Code Filter to filter out Inferred Electronic Annotations (IEA) and generate a new annotation graph for the PL1 Set. The resulting graph seen in Fig. 7 is simpler than the one in Fig. 4 where all available annotations were used regardless of their Evidence Codes. Because the bulk of all annotations consist of IEA annotations the PL1 Set only has 32 out of 564 proteins with non-IEA annotations. Hence, this filtering focuses the PL1 Set on its annotations considered to be of higher quality but at the cost of coverage. Furthermore, the simplification of the graph also matches that of the previously shown term enrichment (using all annotations) thus reinforcing the previous enrichment results.


GRYFUN: a web application for GO term annotation visualization and analysis in protein sets.

Bastos HP, Sousa L, Clarke LA, Couto FM - PLoS ONE (2015)

PL1 Set non-IEA annotation graph for the GO molecular function sub-ontology.Annotation graph subsuming the PL1 (within the CAZy Collection) Set GO molecular function sub-ontology annotations without electronic annotations (IEA).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4368792&req=5

pone.0119631.g007: PL1 Set non-IEA annotation graph for the GO molecular function sub-ontology.Annotation graph subsuming the PL1 (within the CAZy Collection) Set GO molecular function sub-ontology annotations without electronic annotations (IEA).
Mentions: In addition, we used the Evidence Code Filter to filter out Inferred Electronic Annotations (IEA) and generate a new annotation graph for the PL1 Set. The resulting graph seen in Fig. 7 is simpler than the one in Fig. 4 where all available annotations were used regardless of their Evidence Codes. Because the bulk of all annotations consist of IEA annotations the PL1 Set only has 32 out of 564 proteins with non-IEA annotations. Hence, this filtering focuses the PL1 Set on its annotations considered to be of higher quality but at the cost of coverage. Furthermore, the simplification of the graph also matches that of the previously shown term enrichment (using all annotations) thus reinforcing the previous enrichment results.

Bottom Line: This in turn can introduce issues regarding the interpretation of actual functional similarity and overall functional coherence of such a group.One way to mitigate such issues is through the use of visualization and statistical techniques.Therefore, in order to help interpret this annotation heterogeneity we created a web application that generates Gene Ontology annotation graphs for protein sets and their associated statistics from simple frequencies to enrichment values and Information Content based metrics.

View Article: PubMed Central - PubMed

Affiliation: LaSIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.

ABSTRACT
Functional context for biological sequence is provided in the form of annotations. However, within a group of similar sequences there can be annotation heterogeneity in terms of coverage and specificity. This in turn can introduce issues regarding the interpretation of actual functional similarity and overall functional coherence of such a group. One way to mitigate such issues is through the use of visualization and statistical techniques. Therefore, in order to help interpret this annotation heterogeneity we created a web application that generates Gene Ontology annotation graphs for protein sets and their associated statistics from simple frequencies to enrichment values and Information Content based metrics. The publicly accessible website http://xldb.di.fc.ul.pt/gryfun/ currently accepts lists of UniProt accession numbers in order to create user-defined protein sets for subsequent annotation visualization and statistical assessment. GRYFUN is a freely available web application that allows GO annotation visualization of protein sets and which can be used for annotation coherence and cohesiveness analysis and annotation extension assessments within under-annotated protein sets.

No MeSH data available.