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insertions(+) create mode 100644 joss.06624/10.21105.joss.06624.crossref.xml diff --git a/joss.06624/10.21105.joss.06624.crossref.xml b/joss.06624/10.21105.joss.06624.crossref.xml new file mode 100644 index 0000000000..e66165ab47 --- /dev/null +++ b/joss.06624/10.21105.joss.06624.crossref.xml @@ -0,0 +1,208 @@ + + + + 20240605114058-b4e6886f607cd1e62f17b7233a0608305e5ea561 + 20240605114058 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 06 + 2024 + + + 9 + + 98 + + + + GeneScape: A Python package for gene ontology +visualization + + + + Istvan + Albert + https://orcid.org/0000-0001-8366-984X + + + + 06 + 05 + 2024 + + + 6624 + + + 10.21105/joss.06624 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.11245264 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/6624 + + + + 10.21105/joss.06624 + https://joss.theoj.org/papers/10.21105/joss.06624 + + + https://joss.theoj.org/papers/10.21105/joss.06624.pdf + + + + + + Gene ontology: Tool for the unification of +biology + Ashburner + Nature Genetics + 1 + 25 + 10.1038/75556 + 2000 + Ashburner, M., Ball, C. A., Blake, J. +A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., +Dwight, S. S., Eppig, J. T., Harris, M. A., Hill, D. P., Issel-Tarver, +L., Kasarskis, A., Lewis, S., Matese, J. C., Richardson, J. E., +Ringwald, M., Rubin, G. M., & Sherlock, G. (2000). Gene ontology: +Tool for the unification of biology. Nature Genetics, 25(1), 25–29. +https://doi.org/10.1038/75556 + + + The Gene Ontology knowledgebase in +2023 + Consortium + Genetics + 1 + 224 + 10.1093/genetics/iyad031 + 1943-2631 + 2023 + Consortium, T. G. O., Aleksander, S. +A., Balhoff, J., Carbon, S., Cherry, J. M., Drabkin, H. J., Ebert, D., +Feuermann, M., Gaudet, P., Harris, N. L., Hill, D. P., Lee, R., Mi, H., +Moxon, S., Mungall, C. J., Muruganugan, A., Mushayahama, T., Sternberg, +P. W., Thomas, P. D., … Westerfield, M. (2023). The Gene Ontology +knowledgebase in 2023. Genetics, 224(1), iyad031. +https://doi.org/10.1093/genetics/iyad031 + + + AmiGO: online access to ontology and +annotation data + Carbon + Bioinformatics + 2 + 25 + 10.1093/bioinformatics/btn615 + 1367-4803 + 2008 + Carbon, S., Ireland, A., Mungall, C. +J., Shu, S., Marshall, B., Lewis, S., AmiGO Hub, the, & Web Presence +Working Group, the. (2008). AmiGO: online access to ontology and +annotation data. Bioinformatics, 25(2), 288–289. +https://doi.org/10.1093/bioinformatics/btn615 + + + GOATOOLS: A python library for gene ontology +analyses + Klopfenstein + Scientific reports + 1 + 8 + 10.1038/s41598-018-28948-z + 2018 + Klopfenstein, D., Zhang, L., +Pedersen, B. S., Ramı́rez, F., Warwick Vesztrocy, A., Naldi, A., Mungall, +C. J., Yunes, J. M., Botvinnik, O., Weigel, M., & others. (2018). +GOATOOLS: A python library for gene ontology analyses. Scientific +Reports, 8(1), 1–17. +https://doi.org/10.1038/s41598-018-28948-z + + + topGO: Enrichment analysis for gene +ontology + Alexa + Bioconductor + 10.18129/B9.bioc.topGO + 2023 + Alexa, A., & Rahnenfuhrer, J. +(2023). topGO: Enrichment analysis for gene ontology. In Bioconductor. +Bioconductor. +https://doi.org/10.18129/B9.bioc.topGO + + + QuickGO: a web-based tool for Gene Ontology +searching + Binns + Bioinformatics + 22 + 25 + 10.1093/bioinformatics/btp536 + 1367-4803 + 2009 + Binns, D., Dimmer, E., Huntley, R., +Barrell, D., O’Donovan, C., & Apweiler, R. (2009). QuickGO: a +web-based tool for Gene Ontology searching. Bioinformatics, 25(22), +3045–3046. +https://doi.org/10.1093/bioinformatics/btp536 + + + Exploring network structure, dynamics, and +function using NetworkX + Hagberg + Proceedings of the 7th python in science +conference + 2008 + Hagberg, A. A., Schult, D. A., & +Swart, P. J. (2008). Exploring network structure, dynamics, and function +using NetworkX. In G. Varoquaux, T. Vaught, & J. Millman (Eds.), +Proceedings of the 7th python in science conference (pp. +11–15). + + + Shiny: Web application framework for +r + Chang + 2024 + Chang, W., Cheng, J., Allaire, J., +Sievert, C., Schloerke, B., Xie, Y., Allen, J., McPherson, J., Dipert, +A., & Borges, B. (2024). 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    + + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +6624 +10.21105/joss.06624 + +GeneScape: A Python package for gene ontology +visualization + + + +https://orcid.org/0000-0001-8366-984X + +Albert +Istvan + + + + + + +Bioinformatics Consulting Center, Pennsylvania State +University, United States of America + + + + +Department of Biochemistry and Molecular Biology, +Pennsylvania State University, United States of America + + + + +30 +3 +2024 + +9 +98 +6624 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +biology +bioinformatics +functional analysis + + + + + + Summary +

    The Gene Ontology (GO) + (Ashburner + et al., 2000; + Consortium + et al., 2023) is a structured vocabulary that describes gene + products in the context of their associated functions. The ontology + takes the form of a directed graph, where each node defines a term, + and each edge represents a hierarchical relationship between the terms + (the words of the vocabulary).

    +

    For example, in the GO data, GO:0090630 + defines activation of GTPase activity and is a child + of GO:0043547, defined as positive + regulation of GTPase activity which in turn is a child of + GO:0051345 representing positive + regulation of hydrolase activity.

    +

    Gene association files (GAF) are text files used to annotate an + organism’s gene products with Gene Ontology terms, associating + functions to gene products. For example, a GAF file connects a gene + product label, such as ZC3H11B, with multiple + GO terms, such as GO:0046872 or + GO:0016973. The complete human genome GAF + representation contains 288,575 associations of 19,606 gene symbols + with over 18,680 GO terms.

    +

    The + Gene + Ontology Consortium maintains GAF files for various + organisms. Typical genomic analysis protocols generate gene lists that + must be placed in a functional context.

    +
    + + Statement of need +

    The most annotated gene in the human genome, + HTT, currently has 1100 annotations. Thus, even + small lists of genes may have a large number of annotations presenting + an extraordinary challenge for interpretation. There is a clear need + to visualize shared gene functions in an informative manner.

    +

    Web-based tools designed to visualize and filter gene ontology data + include AmiGO + (Carbon + et al., 2008) and QuickGO + (Binns + et al., 2009). Command line tools like + goatools + (Klopfenstein + et al., 2018) support GO term lineage visualization. R packages + like topGO + (Alexa + & Rahnenfuhrer, 2023) implement GO structure visualizations + of enriched GO terms. We are unaware of locally installable software + that allows for interactive filtering and visualization of gene + ontology terms derived from gene lists.

    +

    GeneScape is a Python package that allows users to visualize a list + of genes in the functional context represented by the Gene + Ontology

    +

    GeneScape is distributed both as a command-line tool and as + GUI-enabled standalone software via the + Shiny + platform + (Chang + et al., 2024), making it accessible to a wide range of + users.

    + +

    GeneScape as a Shiny App +

    + +
    +

    GeneScape is distributed with several prebuilt databases for model + organisms including the human, mouse, rat, fruitfly and zebrafish + genomes. To study additional organisms, users must download GAF files + from the Gene Ontology website and create custom databases using the + build subcommand:

    + genescape build --gaf mydata.gaf.gz --index mydata.index.gz +

    For detailed instructions on using the software, users should refer + to the + GeneScape + documentation. A Q&A discussion board is also available + on the GeneScape GitHub page.

    + + Typical usage +

    A typical usage starts with a gene list such as:

    + ABTB3 +BCAS4 +C3P1 +GRTP1 +

    Users can process the list above via the command line or the + Shiny interface. A command line invocation might look like:

    + genescape tree genes1.txt -o output.pdf +

    The command above will produce the image:

    + +

    Ontology subgraph for a gene list +

    + +
    +

    Internally, GeneScape first transforms the input gene list into a + GO term list, where additional information is added to each + term:

    + Coverage,Function,Domain,GO,Genes +1,endopeptidase inhibitor activity,MF,GO:0004866,C3P1 +1,GTPase activator activity,MF,GO:0005096,GRTP1 +1,extracellular space,CC,GO:0005615,C3P1 +1,cytoplasm,CC,GO:0005737,BCAS4 +1,membrane,CC,GO:0016020,ABTB3 +1,PDZ domain binding,MF,GO:0030165,ABTB3 +1,BLOC-1 complex,CC,GO:0031083,BCAS4 +1,"synaptic transmission, glutamatergic",BP,GO:0035249,ABTB3 +1,exploration behavior,BP,GO:0035640,ABTB3 +1,protein heterodimerization activity,MF,GO:0046982,ABTB3 +1,protein stabilization,BP,GO:0050821,ABTB3 +1,activation of GTPase activity,BP,GO:0090630,GRTP1 +1,glutamatergic synapse,CC,GO:0098978,ABTB3 +

    In the next step, GeneScape draws the GO terms as the graph + structure using the Networkx package + (Hagberg + et al., 2008), helping users visualize the functional context + of the genes relative to the larger Gene Ontology.

    +

    Various colors and labels are used to provide additional context + to the nodes in the graph; for example, functions present in the + input genes are colored green. Intermediate nodes are colored by + their category. Node labels display the total annotations and the + number of genes that carry that function.

    + +

    Filtering a large graph for a specific term +

    + +
    +

    In the web interface, users can zoom in and out of the tree. The + software’s command-line version supports generating outputs in + various formats, such as PDF or PNG.

    +

    Since the resulting graphs may also be large, with thousands of + nodes, the main interface provides input widgets that allow users to + interactively reduce the subgraph to nodes for which:

    + + +

    The function definitions match certain patterns.

    +
    + +

    A minimum number of genes share a function.

    +
    + +

    Nodes belong to a specific GO subtree: Biological Process + (BP), Molecular Function (MF), Cellular Component (CC).

    +
    +
    +

    As an example, take the input gene list of just four genes:

    + Cyp1a1 +Sphk2 +Sptlc2 +Smpd3 +

    the resulting functional ontology graph is large with 641 nodes + and 1,007 edges:

    + +

    Very few genes can produce a large ontology tree +

    + +
    +

    Users can reduce the tree to show only terms that match the word + lipid and with at least two genes supporting + the function via the graphical user interface or the command + line:

    + genescape tree -m lipid --mincov 2 genes2.txt -o output.pdf +

    The filtering process will result in a smaller tree with 18 nodes + and 29 edges, focused on the functions that contain the word + “lipid”:

    + +

    Filtering a large graph for a specific term +

    + +
    +

    The software’s primary purpose is to allow users to assess the + functional depth of genes and identify commonalities and differences + in the functional context of these genes.

    +
    +
    + + Acknowledgments +

    We acknowledge support from the Huck Institutes for the Life + Sciences at the Pennsylvania State University.

    +
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