amnona
amnona
agree sample_color_bars is a bit confusing vote for change to sample_highlights 👍
I think you can create a calour Experiment from a data matrix and sample metadata pandas dataframe. just do: xx = calour.Experiment(data=data_matrix, sample_metadata=sample_metadata_dataframe) or better if you are dealing with...
if you want to create an experiment from existing (in memory) data, you should not use ca.read_amplicon() but rather: xx = calour.AmpliconExperiment(data=data_matrix, sample_metadata=sample_metadata_dataframe) for example: (first load an existing experiment...
arghh. sorry about these pesky bugs. can you send me the (pickled) data, samples and features variables so i can recreate and hopefully solve it?
Currently there is no statistical test for multiple group difference in calour :( 1. I usually like to look at the data (all categories) and then do tests on groups...
In theory yes. But since dsFDR is based on permutations, you need the statistic calculation to be fast enough (since it needs to calculate it for 1000 random permutations). What...
i don't have experience with the qiime2 plugin, and especially with the kruwallis test. Let me know how it goes, and if you encounter problems, you can post a question...
should be the default location, other locations are ok
i think this will be left for version 2. currently mac users can split using qiime or qiime2?
added in troubleshooting section