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Journal ArticleDOI

KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases

01 Jul 2011-Nucleic Acids Research (Oxford University Press)-Vol. 39, pp 316-322
TL;DR: A web server, KOBAS 2.0, is reported, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations, which allows for both ID mapping and cross-species sequence similarity mapping.
Abstract: High-throughput experimental technologies often identify dozens to hundreds of genes related to, or changed in, a biological or pathological process. From these genes one wants to identify biological pathways that may be involved and diseases that may be implicated. Here, we report a web server, KOBAS 2.0, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). KOBAS 2.0 can be accessed at http://kobas.cbi.pku.edu.cn.

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Citations
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Journal ArticleDOI
TL;DR: G:Profiler is now capable of analysing data from any organism, including vertebrates, plants, fungi, insects and parasites, and the 2019 update introduces an extensive technical rewrite making the services faster and more flexible.
Abstract: Biological data analysis often deals with lists of genes arising from various studies. The g:Profiler toolset is widely used for finding biological categories enriched in gene lists, conversions between gene identifiers and mappings to their orthologs. The mission of g:Profiler is to provide a reliable service based on up-to-date high quality data in a convenient manner across many evidence types, identifier spaces and organisms. g:Profiler relies on Ensembl as a primary data source and follows their quarterly release cycle while updating the other data sources simultaneously. The current update provides a better user experience due to a modern responsive web interface, standardised API and libraries. The results are delivered through an interactive and configurable web design. Results can be downloaded as publication ready visualisations or delimited text files. In the current update we have extended the support to 467 species and strains, including vertebrates, plants, fungi, insects and parasites. By supporting user uploaded custom GMT files, g:Profiler is now capable of analysing data from any organism. All past releases are maintained for reproducibility and transparency. The 2019 update introduces an extensive technical rewrite making the services faster and more flexible. g:Profiler is freely available at https://biit.cs.ut.ee/gprofiler.

2,959 citations


Cites methods from "KOBAS 2.0: a web server for annotat..."

  • ...There are a several functional enrichment analysis tools such as Enrichr (1), WebGestalt (2), Metascape (3), KOBAS (4) and AgriGO (5) suitable for positioning the novel findings against the body of previous knowledge....

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  • ...There are a several functional enrichment analysis tools such as Enrichr (1), WebGestalt (2), Metascape (3), KOBAS (4) and AgriGO (5) suitable for positioning the novel findings against the body of previous knowledge....

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Journal ArticleDOI
03 Apr 2019-Nature
TL;DR: Transcriptional adaptation, a genetic compensation process by which organisms respond to mutations by upregulating related genes, is triggered by mRNA decay and involves a sequence-dependent mechanism.
Abstract: Genetic robustness, or the ability of an organism to maintain fitness in the presence of harmful mutations, can be achieved via protein feedback loops. Previous work has suggested that organisms may also respond to mutations by transcriptional adaptation, a process by which related gene(s) are upregulated independently of protein feedback loops. However, the prevalence of transcriptional adaptation and its underlying molecular mechanisms are unknown. Here, by analysing several models of transcriptional adaptation in zebrafish and mouse, we uncover a requirement for mutant mRNA degradation. Alleles that fail to transcribe the mutated gene do not exhibit transcriptional adaptation, and these alleles give rise to more severe phenotypes than alleles displaying mutant mRNA decay. Transcriptome analysis in alleles displaying mutant mRNA decay reveals the upregulation of a substantial proportion of the genes that exhibit sequence similarity with the mutated gene's mRNA, suggesting a sequence-dependent mechanism. These findings have implications for our understanding of disease-causing mutations, and will help in the design of mutant alleles with minimal transcriptional adaptation-derived compensation.

679 citations

Journal ArticleDOI
TL;DR: A novel machine learning-based method was introduced, CGPS, which incorporates seven FCS tools and two PT tools into a single ensemble score and intelligently prioritizes the relevant biological pathways.
Abstract: Gene set enrichment (GSE) analysis plays an essential role in extracting biological insight from genome-scale experiments. ORA (overrepresentation analysis), FCS (functional class scoring), and PT (pathway topology) approaches are three generations of GSE methods along the timeline of development. Previous versions of KOBAS provided services based on just the ORA method. Here we presented version 3.0 of KOBAS, which is named KOBAS-i (short for KOBAS intelligent version). It introduced a novel machine learning-based method we published earlier, CGPS, which incorporates seven FCS tools and two PT tools into a single ensemble score and intelligently prioritizes the relevant biological pathways. In addition, KOBAS has expanded the downstream exploratory visualization for selecting and understanding the enriched results. The tool constructs a novel view of cirFunMap, which presents different enriched terms and their correlations in a landscape. Finally, based on the previous version's framework, KOBAS increased the number of supported species from 1327 to 5944. For an easier local run, it also provides a prebuilt Docker image that requires no installation, as a supplementary to the source code version. KOBAS can be freely accessed at http://kobas.cbi.pku.edu.cn, and a mirror site is available at http://bioinfo.org/kobas.

495 citations

Journal ArticleDOI
13 Apr 2017-Nature
TL;DR: It is shown that type 1 T helper (TH1) cells play a crucial role in vessel normalization, and may be a marker and a determinant of both immune checkpoint blockade and anti-angiogenesis efficacy.
Abstract: Blockade of angiogenesis can retard tumour growth, but may also paradoxically increase metastasis. This paradox may be resolved by vessel normalization, which involves increased pericyte coverage, improved tumour vessel perfusion, reduced vascular permeability, and consequently mitigated hypoxia. Although these processes alter tumour progression, their regulation is poorly understood. Here we show that type 1 T helper (TH1) cells play a crucial role in vessel normalization. Bioinformatic analyses revealed that gene expression features related to vessel normalization correlate with immunostimulatory pathways, especially T lymphocyte infiltration or activity. To delineate the causal relationship, we used various mouse models with vessel normalization or T lymphocyte deficiencies. Although disruption of vessel normalization reduced T lymphocyte infiltration as expected, reciprocal depletion or inactivation of CD4+ T lymphocytes decreased vessel normalization, indicating a mutually regulatory loop. In addition, activation of CD4+ T lymphocytes by immune checkpoint blockade increased vessel normalization. TH1 cells that secrete interferon-γ are a major population of cells associated with vessel normalization. Patient-derived xenograft tumours growing in immunodeficient mice exhibited enhanced hypoxia compared to the original tumours in immunocompetent humans, and hypoxia was reduced by adoptive TH1 transfer. Our findings elucidate an unexpected role of TH1 cells in vasculature and immune reprogramming. TH1 cells may be a marker and a determinant of both immune checkpoint blockade and anti-angiogenesis efficacy.

479 citations

Journal ArticleDOI
09 Jul 2020-Cell
TL;DR: The structural variations from the 2,898 accessions that were genotyped based on the graph-based genome and the RNA sequencing data from the representative 26 accessions helped to link genetic variations to candidate genes that are responsible for important traits.

395 citations

References
More filters
Journal ArticleDOI
TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Abstract: SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.

83,420 citations


"KOBAS 2.0: a web server for annotat..." refers methods in this paper

  • ...0, we add two more popular FDR correction methods: Benjamini-Hochberg (40) and Benjamini-Yekutieli (41)....

    [...]

  • ...We used ‘annotate’ to map sequences of upregulated probe sets in CA as well as the entire probe sets to KEGG human genes with default cutoffs and then used ‘identify’ to perform hypergeometric test and Benjamini-Hochberg FDR correction to find significantly enriched pathways and diseases by using the two results of ‘annotate’ as input and background, respectively....

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  • ...In KOBAS 2.0, we add two more popular FDR correction methods: Benjamini-Hochberg (40) and Benjamini-Yekutieli (41)....

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Journal ArticleDOI
TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Abstract: Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.

35,225 citations

Journal ArticleDOI
TL;DR: By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
Abstract: DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.

31,015 citations


"KOBAS 2.0: a web server for annotat..." refers background or methods in this paper

  • ...DAVID can perform only ID mapping to rhesus genes in its two pathway databases (KEGG PATHWAY and Panther) and as a result, identified no statistically significantly enriched pathways or diseases (with default options and corrected P 0.05)....

    [...]

  • ...We then used both DAVID (15,16) and KOBAS 2....

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  • ...Except for DAVID, all these tools integrate limited pathway and disease databases (for a comparison, see Supplementary Table S1)....

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  • ...A growing number of tools have been developed for pathway and disease identification, including, but not limited to, MAPPFinder (13), EASE (14), DAVID (15,16), ArrayXPath (17), WebGestalt (18), FuncCluster (19), PageMan (20), GENECODIS (21,22), GeneTrail (23), g:Profiler (24), FunNet (25) and PaLS (26)....

    [...]

  • ...We then used both DAVID (15,16) and KOBAS 2.0 to annotate these probe sets and identify enriched pathways and diseases by using the entire probe sets on the chip as background....

    [...]

Journal ArticleDOI
TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Abstract: Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).

24,024 citations

Journal ArticleDOI
TL;DR: The survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
Abstract: Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

13,102 citations


"KOBAS 2.0: a web server for annotat..." refers background or methods in this paper

  • ...DAVID can perform only ID mapping to rhesus genes in its two pathway databases (KEGG PATHWAY and Panther) and as a result, identified no statistically significantly enriched pathways or diseases (with default options and corrected P 0.05)....

    [...]

  • ...We then used both DAVID (15,16) and KOBAS 2....

    [...]

  • ...Except for DAVID, all these tools integrate limited pathway and disease databases (for a comparison, see Supplementary Table S1)....

    [...]

  • ...A growing number of tools have been developed for pathway and disease identification, including, but not limited to, MAPPFinder (13), EASE (14), DAVID (15,16), ArrayXPath (17), WebGestalt (18), FuncCluster (19), PageMan (20), GENECODIS (21,22), GeneTrail (23), g:Profiler (24), FunNet (25) and PaLS (26)....

    [...]

  • ...We then used both DAVID (15,16) and KOBAS 2.0 to annotate these probe sets and identify enriched pathways and diseases by using the entire probe sets on the chip as background....

    [...]