-
Hi
Could you please clarify if you transform your samples before plotting PCA/PCoA?
Thanks
Marwa
-
First, thanks for this extremely useful package and detailed explanations on tree metrics and visualizations in treespace as well as assessments of those visualizations.
I have a question about the…
-
Hello!
First of all, this is an awesome package, and thank you so much!
I constructed 6 ordination plots with my data, and I am trying to collect them together. However, although I have tried mu…
-
il faudrait qu'on soit bien calés sur les 2 premiers axes de la PCOA en termes d'interprétation. Qu'en dis-tu Olivier?
-
# 降维/排序分析(ordination analysis)
Ordination analysis(排序分析)是生态学和统计学领域中用于分析和解释多变量数据的方法之一。这个方法通常被用于探索和可视化生态学或生物学数据中的pattern,尤其是在物种组成和环境因素之间的关系方面。
[https://asa-blog.netlify.app/p/ordination-analysis/](htt…
-
- **LDA**
- Remove `--input_data_type` parameter.
- utilize argparse checks for relevant input files for bubble plots.
- Consolidate figure sizes for LDA and LDA bubble plots.
- Add optional…
-
Hello!
I'm analysing the trunk's microbiome of a tree (MiSeq 16S V4). Since it's woody tissue, is expected to have very low diversity, therefore, my ASV abundance table has samples with very low fe…
-
I was taking a look through the source to reconcile some discrepancies in how I was computing explained variance in my own code for PCoA. I noticed that around line 99 of `_principle_coordinate_analys…
-
Greetings,
I am working on a microbiomes project and did an principal coordinates analysis in Phyloseq with the following script:
ordu = ordinate(qd.red, "PCoA", "unifrac", weighted = TRUE)
p = pl…
-
Hello,
I am using R version 4.1.1 and microbiotaPair version 0.0.2
I am trying to run the example
`data(physeq_data)`
`physeq