How to use plotly to generate interactive ggpicrust2 plots

[ScarlettPegany]

Hello, I discovered your tool by chance, and it's exactly what I've been looking for. I encountered an issue when running my data, but I was able to resolve it by referring to the issue section (I used the solution proposed in #65). Our professor asked if there is a way to visualize pathway_errorbar, heatmap, and PCA using Plotly (He wants us to become familiar with interactive plots.).

Could you please assist me with this? I tried using ChatGPT, but I couldn't successfully convert it.

Thank you.

[cafferychen777]

Dear @ScarlettPegany,

Thank you for reaching out and for your kind words about our package.

Regarding your request, due to limitations in Plotly's support for combined plots, I attempted a conversion but was only successful with pathway_heatmap. You can make this heatmap interactive using the following method:

p <- pathway_heatmap()
ggplotly(p)

I apologize for any inconvenience this might have caused.

However, I'd like to suggest you explore my other package, MicrobiomeStat. Almost all of its visualizations are seamlessly integrated with Plotly. You can find more details and access it at https://www.microbiomestat.wiki/.

I hope this helps! If you have further questions, feel free to ask.

Best regards,

Chen YANG

[ScarlettPegany]

Is there a way to zoom in on the different plots without using my cursor, perhaps by adjusting the width, height, or other parameters to ensure the plot is readable

[cafferychen777]

Maybe you can use Adode Illustrator？

[ScarlettPegany]

@cafferychen777 : Yes, that's a good idea.
In the case of exploratory analysis, which dataset would be the most meaningful to use? Is it MetaCyc, KO abundance, or KEGG abundance? I truly need to comprehend the distinctions among these three.
I've already read your comments in issue #64, but I'm still struggling to grasp the role of MetaCyc in the context of functional
analysis prediction compared to the other two.

One last question: how do I determine the appropriate test to use, whether it's DESeq2, edgeR, ALDEx2, etc.?

[Aristotle1992]

@ScarlettPegany I am just a little curious, how were you able to increase the font size of the pathway error bar plot? Thanks

[ScarlettPegany]

@ScarlettPegany I am just a little curious, how were you able to increase the font size of the pathway error bar plot? Thanks

I used Adode Illustrator. If you come across a script that allows you to do that, please don't hesitate to share it.

[cafferychen777]

Dear @ScarlettPegany,

Thank you for reaching out with your questions. Let me address each one in turn:

1. Dataset Selection: All three datasets - MetaCyc, KO abundance, and KEGG abundance - are meaningful in their own right. The best choice often depends on the specific context and objective of your analysis.

2. Role of MetaCyc: Regarding your question about the role of MetaCyc in functional analysis prediction, I'd recommend reaching out to the managers or administrators of the MetaCyc database. They would be in a better position to provide detailed insights into the nuances of MetaCyc compared to KO abundance and KEGG abundance.

3. Test Selection: Personally, I have a preference for ALDEx2 and LinDA. For analyses involving three or more groups, I'd recommend ALDEx2. For comparisons between two groups, LinDA would be my choice.

I hope this clarifies your queries. Please let me know if you have any more questions or if there's any other way I can assist you.

Best regards,
Chen YANG

[Aristotle1992]

@ScarlettPegany In order toincrease the font size, I would suggest you fork the source code and then edit the parameters necessary. That how i was able to increase the font size of mine figure. Way more better and faster i would think compared to using adobe