Hello, After running gneiss I identified two outliers by looking at the residual plot and also at the proportion plot. I wanted to remove them from the analysis because they are quite different values from the rest so I filtered those two samples from the table with: qiime feature-table filter-sam…

Glad that the residual plots are useful. It looks like there are only two samples in your table, namely 1157B_FR900_T4, and 1162B_FR900_T2. Are these the samples that you want to filter out? If so, the filtering criteria may need to be inverted.

Hi, Yes, precisely! I didn't realise I had to use --p-exclude instead of --p-where. Thanks!

Hi there, I am having a similar issue that I'm hoping someone can help me out with. I'm using American Gut Project data. I have imported an OTU table (.biom), and created the "FeatureTable[Frequency]" and "FeatureData[Taxonomy]" file, collapsed the taxa at the p2 level, created a composition table,…

Hey there @Calliope_Holingue ! [image] Calliope_Holingue: However, when I run the ols-regression I receive the following error: Thanks for providing all those commands above, but, I didn't actually see this command listed in your script - can you please copy-and-paste that here? Otherwise we …

Sorry about that! Here is what I ran: qiime gneiss ols-regression --p-formula "sample_name_full + sleep_duration_r" --i-table /users/cholingu/agp_data/projects/sleep_duration/balances.collapsedp2.qza --i-tree /users/cholingu/agp_data/projects/sleep_duration/hierarchy.collapsedp2.qza --m-metadata-fi…

@Calliope_Holingue just as a sanity check, you were able to sanity check the tables (i.e. no extremely low abundance / variance features)?

Hi @mortonjt , this was a good suggestion. I further filtered the features and samples (--p-min-frequency 1500 for samples, --p-min-frequency 10 for features, --p-min-samples 2 for features) and the regression ran successfully. Can you clarify how to check for low abundance / variance features? Is t…

[image] Calliope_Holingue: how to check for low abundance / variance features @mortonjt might have some other suggestions here, but the first thing that comes to my mind is running feature-table summarize , then looking at the "Feature Detail" tab (see the MP tutorial for an example ). In the l…

yes, thank you, this is very helpful! thanks for your help with this.

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