Hello everyone!
I used this code:
plot_bar(data, x = "SampleID", fill = "Class")
and I got a nice barplot, but colors are alike and its hard to distinguish Classes .
How can I make each Class (taxon) a different color?
Thanks
Hello everyone!
I used this code:
plot_bar(data, x = "SampleID", fill = "Class")
and I got a nice barplot, but colors are alike and its hard to distinguish Classes .
How can I make each Class (taxon) a different color?
Thanks
HI @alla , is better try to help you if put the reprex.
Try with this
head(dput(data, 100)) #
For more control in which color you want, you could addscale_fill_manual()
If you have 20 taxon you need 20 color. Don't forget the color for NA value or omit.
For select better color (RGB) check this page and put the number with # for each color.
library(tidyverse)
ggplot(data,x = "SampleID", fill = "Class") +
geom_bar()+
scale_fill_manual(values = c('red', 'blue', 'green','red', 'blue',
'#AA9539', '#256F5C', '#AA6339',' #3E3175', '#D6D214', #You could change manual color
'red', 'blue', 'green','red', 'blue',
'red', 'blue', 'green','red', 'blue',
'red', 'blue', 'green','red', 'blue'))
Oh, I am sorry.
So, data we got is from 16s sequencing.
I did the qiime2 analysis, got all artifacts for further analysis in Rstudio.
Then created a phyloseq object (like herehttps://forum.qiime2.org/t/tutorial-integrating-qiime2-and-r-for-data-visualization-and-analysis-using-qiime2r/4121) , did some cleaning with Decontam package.
So data looks like that:
phyloseq-class experiment-level object
otu_table() OTU Table: [ 1045 taxa and 42 samples ]
sample_data() Sample Data: [ 42 samples by 8 sample variables ]
tax_table() Taxonomy Table: [ 1045 taxa by 7 taxonomic ranks ]
phy_tree() Phylogenetic Tree: [ 1045 tips and 1044 internal nodes ]
Dont worry about this! Is difficult understand well the situation without correct data example.
Check how to put reproducible example, take you time for make this.
Thank you for your answer!
I try it, but seems I have some issue my phyloseq object is S4 type.
Error in fortify()
:
! data
must be a <data.frame>, or an object coercible by fortify()
, not an S4
object with class .
Maybe if you have a phyloseq object like this could help:
This topic was automatically closed 42 days after the last reply. New replies are no longer allowed.
If you have a query related to it or one of the replies, start a new topic and refer back with a link.