Limits...
AnGeLi: A Tool for the Analysis of Gene Lists from Fission Yeast.

Bitton DA, Schubert F, Dey S, Okoniewski M, Smith GC, Khadayate S, Pancaldi V, Wood V, Bähler J - Front Genet (2015)

Bottom Line: AnGeLi searches for significant enrichments among multiple qualitative and quantitative information sources, including gene and phenotype ontologies, genetic and protein interactions, numerous features of genes, transcripts, translation, and proteins such as copy numbers, chromosomal positions, genetic diversity, RNA polymerase II and ribosome occupancy, localization, conservation, half-lives, domains, and molecular weight among others, as well as diverse sets of genes that are co-regulated or lead to the same phenotypes when mutated.AnGeLi offers a rigorous yet flexible statistical analysis platform for rich insights into functional enrichments and biological context for query gene lists, thus providing a powerful exploratory tool through which S. pombe researchers can uncover fresh perspectives and unexpected connections from genomic data.AnGeLi is freely available at: www.bahlerlab.info/AnGeLi.

View Article: PubMed Central - PubMed

Affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.

ABSTRACT
Genome-wide assays and screens typically result in large lists of genes or proteins. Enrichments of functional or other biological properties within such lists can provide valuable insights and testable hypotheses. To systematically detect these enrichments can be challenging and time-consuming, because relevant data to compare against query gene lists are spread over many different sources. We have developed AnGeLi (Analysis of Gene Lists), an intuitive, integrated web-tool for comprehensive and customized interrogation of gene lists from the fission yeast, Schizosaccharomyces pombe. AnGeLi searches for significant enrichments among multiple qualitative and quantitative information sources, including gene and phenotype ontologies, genetic and protein interactions, numerous features of genes, transcripts, translation, and proteins such as copy numbers, chromosomal positions, genetic diversity, RNA polymerase II and ribosome occupancy, localization, conservation, half-lives, domains, and molecular weight among others, as well as diverse sets of genes that are co-regulated or lead to the same phenotypes when mutated. AnGeLi uses robust statistics which can be tailored to specific needs. It also provides the option to upload user-defined gene sets to compare against the query list. Through an integrated data submission form, AnGeLi encourages the community to contribute additional curated gene lists to further increase the usefulness of this resource and to get the most from the ever increasing large-scale experiments. AnGeLi offers a rigorous yet flexible statistical analysis platform for rich insights into functional enrichments and biological context for query gene lists, thus providing a powerful exploratory tool through which S. pombe researchers can uncover fresh perspectives and unexpected connections from genomic data. AnGeLi is freely available at: www.bahlerlab.info/AnGeLi.

No MeSH data available.


Workflows in AnGeLi. (Top – blue) Data entry: the user pastes a query gene list and has the option to add user-defined gene sets and/or select the background gene set (default = PC; protein-coding genes). If no additional gene sets are added, under default settings, 7554 features of the AnGeLi knowledgebase will be analyzed (7505 binary, and 49 metric features), because 1277 GO Molecular Function, 797 GO Cellular Component, and 4 Genetic and Physical Interactions (BioGRID) features are excluded by default (9632 features in total). If any user-defined gene sets are added, the database is augmented accordingly. (Middle – green) Statistical parameter settings: the user selects GO category (default = BP; Biological Process), a method for multiple testing correction (default = FDR) and the desired p-value threshold (default = 0.01). The users can also specify whether to perform the pairwise interaction enrichment analysis (default = No), set the desired number of permutations accordingly (default = 1000), and adjust the p-value to account for multiple testing. (Bottom – red) Data processing: AnGeLi performs gene list enrichment analysis based on user input and reports any significant functional enriched features, along with associated information.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4644808&req=5

Figure 1: Workflows in AnGeLi. (Top – blue) Data entry: the user pastes a query gene list and has the option to add user-defined gene sets and/or select the background gene set (default = PC; protein-coding genes). If no additional gene sets are added, under default settings, 7554 features of the AnGeLi knowledgebase will be analyzed (7505 binary, and 49 metric features), because 1277 GO Molecular Function, 797 GO Cellular Component, and 4 Genetic and Physical Interactions (BioGRID) features are excluded by default (9632 features in total). If any user-defined gene sets are added, the database is augmented accordingly. (Middle – green) Statistical parameter settings: the user selects GO category (default = BP; Biological Process), a method for multiple testing correction (default = FDR) and the desired p-value threshold (default = 0.01). The users can also specify whether to perform the pairwise interaction enrichment analysis (default = No), set the desired number of permutations accordingly (default = 1000), and adjust the p-value to account for multiple testing. (Bottom – red) Data processing: AnGeLi performs gene list enrichment analysis based on user input and reports any significant functional enriched features, along with associated information.

Mentions: AnGeLi provides the ability to choose a background gene population as a reference for the statistical analyses based on the query gene list. This option allows tailoring of the analysis to the context of the gene list of interest, which can greatly increase the accuracy and sensitivity of the analysis. For example, a query list from an experiment which has only considered protein-coding genes should be analyzed with the protein-coding gene background. As another example, query genes derived from phenotypic screens with the deletion mutant library will all be non-essential, which would skew the statistics if all genes were used as background. AnGeLi offers six pre-set background options, covering all common scenarios: protein-coding genes (default), all annotated genes, non-coding RNA genes, genes with associated GO terms, genes with associated phenotypes, and non-essential genes. In addition, users can provide their own bespoke background gene list to tailor the analysis to their particular requirements. An overview of AnGeLi’s steps for data entry, statistical tests and data processing is presented in Figure 1.


AnGeLi: A Tool for the Analysis of Gene Lists from Fission Yeast.

Bitton DA, Schubert F, Dey S, Okoniewski M, Smith GC, Khadayate S, Pancaldi V, Wood V, Bähler J - Front Genet (2015)

Workflows in AnGeLi. (Top – blue) Data entry: the user pastes a query gene list and has the option to add user-defined gene sets and/or select the background gene set (default = PC; protein-coding genes). If no additional gene sets are added, under default settings, 7554 features of the AnGeLi knowledgebase will be analyzed (7505 binary, and 49 metric features), because 1277 GO Molecular Function, 797 GO Cellular Component, and 4 Genetic and Physical Interactions (BioGRID) features are excluded by default (9632 features in total). If any user-defined gene sets are added, the database is augmented accordingly. (Middle – green) Statistical parameter settings: the user selects GO category (default = BP; Biological Process), a method for multiple testing correction (default = FDR) and the desired p-value threshold (default = 0.01). The users can also specify whether to perform the pairwise interaction enrichment analysis (default = No), set the desired number of permutations accordingly (default = 1000), and adjust the p-value to account for multiple testing. (Bottom – red) Data processing: AnGeLi performs gene list enrichment analysis based on user input and reports any significant functional enriched features, along with associated information.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644808&req=5

Figure 1: Workflows in AnGeLi. (Top – blue) Data entry: the user pastes a query gene list and has the option to add user-defined gene sets and/or select the background gene set (default = PC; protein-coding genes). If no additional gene sets are added, under default settings, 7554 features of the AnGeLi knowledgebase will be analyzed (7505 binary, and 49 metric features), because 1277 GO Molecular Function, 797 GO Cellular Component, and 4 Genetic and Physical Interactions (BioGRID) features are excluded by default (9632 features in total). If any user-defined gene sets are added, the database is augmented accordingly. (Middle – green) Statistical parameter settings: the user selects GO category (default = BP; Biological Process), a method for multiple testing correction (default = FDR) and the desired p-value threshold (default = 0.01). The users can also specify whether to perform the pairwise interaction enrichment analysis (default = No), set the desired number of permutations accordingly (default = 1000), and adjust the p-value to account for multiple testing. (Bottom – red) Data processing: AnGeLi performs gene list enrichment analysis based on user input and reports any significant functional enriched features, along with associated information.
Mentions: AnGeLi provides the ability to choose a background gene population as a reference for the statistical analyses based on the query gene list. This option allows tailoring of the analysis to the context of the gene list of interest, which can greatly increase the accuracy and sensitivity of the analysis. For example, a query list from an experiment which has only considered protein-coding genes should be analyzed with the protein-coding gene background. As another example, query genes derived from phenotypic screens with the deletion mutant library will all be non-essential, which would skew the statistics if all genes were used as background. AnGeLi offers six pre-set background options, covering all common scenarios: protein-coding genes (default), all annotated genes, non-coding RNA genes, genes with associated GO terms, genes with associated phenotypes, and non-essential genes. In addition, users can provide their own bespoke background gene list to tailor the analysis to their particular requirements. An overview of AnGeLi’s steps for data entry, statistical tests and data processing is presented in Figure 1.

Bottom Line: AnGeLi searches for significant enrichments among multiple qualitative and quantitative information sources, including gene and phenotype ontologies, genetic and protein interactions, numerous features of genes, transcripts, translation, and proteins such as copy numbers, chromosomal positions, genetic diversity, RNA polymerase II and ribosome occupancy, localization, conservation, half-lives, domains, and molecular weight among others, as well as diverse sets of genes that are co-regulated or lead to the same phenotypes when mutated.AnGeLi offers a rigorous yet flexible statistical analysis platform for rich insights into functional enrichments and biological context for query gene lists, thus providing a powerful exploratory tool through which S. pombe researchers can uncover fresh perspectives and unexpected connections from genomic data.AnGeLi is freely available at: www.bahlerlab.info/AnGeLi.

View Article: PubMed Central - PubMed

Affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.

ABSTRACT
Genome-wide assays and screens typically result in large lists of genes or proteins. Enrichments of functional or other biological properties within such lists can provide valuable insights and testable hypotheses. To systematically detect these enrichments can be challenging and time-consuming, because relevant data to compare against query gene lists are spread over many different sources. We have developed AnGeLi (Analysis of Gene Lists), an intuitive, integrated web-tool for comprehensive and customized interrogation of gene lists from the fission yeast, Schizosaccharomyces pombe. AnGeLi searches for significant enrichments among multiple qualitative and quantitative information sources, including gene and phenotype ontologies, genetic and protein interactions, numerous features of genes, transcripts, translation, and proteins such as copy numbers, chromosomal positions, genetic diversity, RNA polymerase II and ribosome occupancy, localization, conservation, half-lives, domains, and molecular weight among others, as well as diverse sets of genes that are co-regulated or lead to the same phenotypes when mutated. AnGeLi uses robust statistics which can be tailored to specific needs. It also provides the option to upload user-defined gene sets to compare against the query list. Through an integrated data submission form, AnGeLi encourages the community to contribute additional curated gene lists to further increase the usefulness of this resource and to get the most from the ever increasing large-scale experiments. AnGeLi offers a rigorous yet flexible statistical analysis platform for rich insights into functional enrichments and biological context for query gene lists, thus providing a powerful exploratory tool through which S. pombe researchers can uncover fresh perspectives and unexpected connections from genomic data. AnGeLi is freely available at: www.bahlerlab.info/AnGeLi.

No MeSH data available.