How to make a plot with gProfileR results?
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3.7 years ago
Biologist ▴ 230

I have a list of genes and to get pathways from that I used gProfileR package.

library(gProfileR)
pathways <- gprofiler(genes, organism = "hsapiens", ordered_query = F,
          significant = T, exclude_iea = F, underrep = F, evcodes = F, region_query = F)

The above function gave me list of pathways and saved that results in csv file. Results from gProfileR looks like this gProfileR results

I would like to know how to make a plot out of those results?

RNA-Seq gprofiler geneexpression pathways plot • 4.9k views
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Do not paste links to screenshots of tabular data, it's multiple unnecessary layers over something that is far easier to showcase in your post. See

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In this tutorial, they have used web-based g:Profiler for the enrichment analysis and cytoscope for the representation.

It may help you.

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3.2 years ago

You might want to check the new gprofiler2 package we have at CRAN. This new R package will allow to make the same manhattan plot visualisations as the gprofiler website does.

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Interesting! Is there a vignette illustrating gProfileR2's functionality somewhere?

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There is no vignette yet, but getting a first interactive visualisation is as simple as

gostres <- gost(query = c("Klf4", "Pax5", "Sox2", "Nanog"), organism = "mmusculus")
gostplot(gostres)

You can get a static image using gostplot(gostres, interactive = F) Check ?gostplot for more options to customize the plot.

And if you have chosen the functions you want to highlight, then you can generate a good quality image using the following commands:

p <- gostplot(gostres, interactive = FALSE)
publish_gostplot(p, highlight_terms = c("GO:0001010", "WP:WP1763"))
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Welcome to Biostars and thank you for the contribution! Please use the formatting bar (especially the code option) to present your post better. You can use backticks for inline code (`text` becomes text), or select a chunk of text and use the highlighted button to format it as a code block. I've done it for you this time.
code_formatting

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Here is the link you can learn from. They have created a proper tutorial.

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