Closed shigdon closed 6 years ago
HEllo @shigdon,
Try this:
library(metacoder)
library(readr)
raw_data <- read_csv(file = "my/file/path")
obj <- parse_tax_data(raw_data, class_cols = 2:8)
n_obs(obj, "tax_data") # Count number of rows in table for each taxon
heat_tree(obj,
node_label = taxon_names,
node_size = n_obs,
node_color = n_obs)
Let me know if you have problems
Thank you very much @zachary-foster ! I now have a beautiful starting point for the plot. I will continue to use and explore the features of this package!
Great, thanks!
Hello @zachary-foster,
I have microbial classification data that was generated using Sourmash, and now I would like to visualize with metacoder. I am struggling to read in the taxmap object file based on the input
csv
file format. The data I am trying to read in as a taxmap object has the following format (sample_id, superkingdom, phylum, class, order, family, genus, species).Here are two example lines within my output file:
What I wish to do is count the number of observations for each level of taxonomic classification across all of my samples and visualize the number of observations for each classification level within my population of sequenced microbial isolates.
I have been trying to learn by following your https://cran.r-project.org/web/packages/metacoder/vignettes/introduction.html, but my data does not seem to be in the same format as the
hmp_otus
file.Is there a way to use
metacoder
andtaxa
to parse the sourmash classification data I have described to generate counts that can be visualized as a heat tree, or do I need to somehow generate counts first?