How to create a relative abundance barplot with ggplot2

This video was created for the 2022 SFSU Science Coding Immersion Program (SPIC).
It shows how to create barplot showing relative abundances of bacteria with ggplot2 and other tidyverse functions in the R programming language.
More details can be found in the associated GitHub repository:
github.com/surh/scip_barplot

[@user-zc6bv8ej9g]

Thank for the vdo. Please keep this type of tutorial vdo coming.

[@user-dp7fj5qd1d]

Thank you for your teaching and sharing. It helps me a lot. Really appreciate.

[@sofiahernandezvivar6893]

Thank you so much for this video!! so clear

[@safiyayakubu2219]

Amazing video. Thank you for sharing. Please make more of these videos on microbiome analyses. e.g beta diversity, pcoa, NMDS, community heat map, serial group comparisons etc

[@gustavsloris]

amazing, thank you! combining all the metabarcoding data in one large table and visualizing with ggplot is much more handy to work with than phyloseq. best regards :)

[@cristianjaviermena6955]

Gracias por este video hermanoo!! no tiene abuela este cientifico!!!

[@playstation4nobplayer892]

Thank you for your video, and I really enjoy and successfully plotted the graph through the tutorial. Anyway, if I apply it to the real work, I would like to know how you calculated the aboundancy %?

[@ginalaspada3521]

😃thank you

[@grazieleruas]

Gracias

[@meseretmuche6984]

remarkable lecture Dear Dr, please share us if you have video lecture related to indicator species analysis in r

[@sunirmalsheet9544]

Thank you for your video. Could you tell the how to get the mean abundence percentage table?

[@amrsalaheldinabdallahhammo663]

How to plot the relative abundance of the most abundant genera (with a mean relative abundance > 1% in all samples? please

[@rishikeshdash12]

Can you tell me which package can be used for prevalence calculation for Microbiome Data.

[@gamraoueslati6914]

Thank you for the video. I just would love to know who you imported the data, and if it should be tsv format? Thanks

[@sur9362]

All the data and code is the github repo github.com/surh/scip_barplot The data is in tsv format so I used the read_tsv function of the readr package

[@TheSalinascrime]

How were you able to obtain the mean abundance to be able to reorder the Phylum?

[@sur9362]

There is more than one way to do it. You can see how I did it in the extended_example.Rmd file of the GitHub repo. Or go to this link github.com/surh/scip_barplot/blob/a775e0d97b47e8dd40498b6713016bbb7e045003/extended_example.Rmd#L285-L301

[@justicetresorngomngom6822]

Hi Thank you for your video, please i would like to know the metagenomic analysis tool that you used and why your OTU ID are coded because mine are long numeric number and i used QIIME2

[@sur9362]

the OTUs and samples are subset of the data from this paper (www.nature.com/articles/nature11237), we built the OTUs with usearch

[@abimbolaenitan129]

How can I get the diversity based on this?

[@dianamamawal4664]

Hi what if i have 50 legends? Cannot do it with rcolorbrewer and rainbow color is not that presentable.

[@sur9362]

I'm general it is not a good idea to represent that many levels with color, the human eye and brain just can't distinguish that many times. Ten is already pushing it and that is my common limit. You should think how to group those 50 levels in a meaningful way. If you really need to show 50 different groups (which generally you don't) then this type of barplot is not the right plot.