cafferychen777
commented
5 months ago Dear Alan,
Thank you for reaching out and for using ggpicrust2 to analyze your PICRUSt2 output data. I appreciate your detailed questions.
Regarding the warnings you encountered, I'd like to assure you that these are typical in the analysis process and generally do not have a significant impact on the overall results.
For the first warning about feature data filtering, it's common in bioinformatics pipelines to encounter features with low non-zero values. While these features have limited statistical power, their presence is a normal part of diverse datasets and doesn't necessarily compromise the analysis. If you wish to filter them, doing so directly in the abundance file (TSV format) is a standard approach. However, it's not always necessary unless they significantly skew your results or if you have specific reasons for stringent data curation.
For the second point regarding group comparisons, editing the abundance file for pairwise comparisons is indeed a straightforward method. It allows you to focus on specific groups of interest. Remember to adjust the metadata file accordingly to ensure consistency between your data and metadata.
Lastly, the warning about the row number not being a multiple of vector length often arises due to mismatches in data dimensions or when combining datasets with different lengths. It's a common warning in data processing and, in most cases, doesn't critically affect the analysis outcome.
In summary, these warnings are part of routine data analysis and do not necessarily indicate a major problem with your analysis or data. Feel free to proceed with your analysis, keeping these points in mind.
Best wishes in your research, and don't hesitate to reach out if you have further questions.
Kind regards,
Chen YANG
pig-raffles
Hi,
Thanks for creating this excellent package for analysing PICRUSt2 output data. I have been looking for something like this for a while now.
I have run the analysis main pipeline (ggpicrust2()) with a couple of different data sets and have run into some error messages that I have some questions about.
The first question is about filtering the feature data. I generally get the following warning when running the pipeline:
"In MicrobiomeStat::linda(abundance, LinDA_metadata_df, formula = "~Group_groupnonsense", : Some features have less than 3 nonzero values! They have virtually no statistical power. You may consider filtering them in the analysis!"
Do you have any advice on how best to filter the feature data. Is it just a case of opening the abundance file (TSV format) and editing it to remove these features/functions? For a data set of 10 individuals split into two treatment groups, would I filter out functions that have nonzero values for only 3 or less individuals out of the 10?
My second issue is about the number of groups I want to compare. Currently the PICRUSt2 output data I wish to use is for 4 different groups and I would like to filter this down to merely pairwise comparisons between groups. Would the simplest way of doing this be, again, to edit the abundance file, filtering out any individuals not from the pairwise comparison I wish to make. Would I also need to alter the metadata file as well?
Finally, I get also get the warning:
"In cbind(sample = colnames(sub_relative_abundance_mat), group = Group, : number of rows of result is not a multiple of vector length (arg 2)"
What could be causing this?
Thank you for your time and any help you can offer,
Best wishes,
Alan