Timeline for How to get the GO information for all the human genes?
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| May 9, 2020 at 15:27 | history | edited | 0x90 | CC BY-SA 4.0 |
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| S May 8, 2020 at 20:36 | history | suggested | Glorfindel | CC BY-SA 4.0 |
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| Feb 19, 2020 at 16:43 | history | edited | 0x90 | CC BY-SA 4.0 |
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| Feb 16, 2020 at 16:14 | comment | added | 0x90 | @MatteoFerla thanks. Let me know if you have a working example. I found GOATOOLS: nature.com/articles/s41598-018-28948-z | |
| Feb 16, 2020 at 15:04 | history | edited | 0x90 | CC BY-SA 4.0 |
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| Feb 16, 2020 at 11:32 | comment | added | Matteo Ferla | GO terms are used routinely to cluster genes for enrichment analysis. There are three categories, location, function and process, and a gene/protein will have one or more descendants (it's a hierarchical ontology). There are online tools that classify genes, such as GOrilla or Reactome. Programmatically you can use say Goatools in Python. There is a R package (don't recall name). And I think a Julia. | |
| Feb 16, 2020 at 4:28 | history | edited | 0x90 | CC BY-SA 4.0 |
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| Feb 15, 2020 at 14:02 | history | edited | 0x90 | CC BY-SA 4.0 |
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| Feb 15, 2020 at 13:05 | comment | added | Matteo Ferla | Have you looked at GO annotations? They are an hierarchical annotation for gene function. For enzymes the EC numbers are also an option. PFam is for structural domains, which generally align with function. | |
| Feb 15, 2020 at 8:31 | comment | added | Devon Ryan | If you really need ALL genes then you won't find such a database, because we don't know all of their functions. | |
| Feb 15, 2020 at 6:17 | history | edited | 0x90 | CC BY-SA 4.0 |
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| Feb 14, 2020 at 23:58 | history | asked | 0x90 | CC BY-SA 4.0 |