Comments (5)
Hi @sarpiens,
The argument zero_cut
could help. The manual has stated that “ Taxa with proportion of zeroes greater than zero_cut will be excluded in the analysis”, therefore, to remove more low abundant taxa, setting a smaller value to zero_cut
would work.
Best,
Huang
from ancombc.
Thanks for the quick response,
The thing is that in some cases I also have ASVs, that seem "truly" abundant in one group, but absent on the other one. For example:
ASV/ /P1_1/ P1_2/ P1_3/ P1_4/ P1_5/
ASV_29/ /449/ 717/ 931/ 657/ 371/
ASV/ /P2_1/ P2_2/ P2_3/ P2_4/ P2_5
ASV_29/ 0/ 0/ 0/ 1/ 0/
And thus I'm worried that setting a smaller value to zero_cut, would remove this ASVs from the analysis too. Because of this I was thinking to apply some filtering step, something like prune ASV that in total have less that 80 counts, to filter those Low abundant ASVs like ASV_2 or ASV_726, but keeping ASVs like ASV_29. But I don't know if it would be better to apply this filter before or after the analysis with ancombc, because I'm worried that filtering these elements prior to the analysis would interfere in the normalization process.
In the original phyloseq object I have 1303 ASVs, but If I remove ASVs with counts < 80 counts for all samples, I keep 437 ASVs.
Thanks in advance
from ancombc.
I also wonder if filtering abundant taxa would interfere in the normalization process, in the case that I also wanted to filter elements with incomplete taxonomies that account for an important part of the counts, in the case that a wanted to repeat the analysis at higher taxonomic levels(genus, family, order,etc).
I'm new new to the CoDa and ANCOM-BC paradigm, so any help is very appreciated!
Thanks in advance
from ancombc.
Thank you for your great suggestion, @sarpiens !
Yes, I think it makes a lot of sense to filter ASV by its total observed abundance. So far it can be done in the data-preprocessing step, for example, QIIME2 has the corresponding filtering steps when you generate the feature table (ASV/OTU table) from raw sequencing data (fastq) files. We will have that feature available in the ANCOMBC function in the next update.
For your second question, yes, theoretically, filtering taxa will not affect the following normalization step.
Best,
Huang
from ancombc.
Thanks a lot!
from ancombc.
Related Issues (20)
- R session aborted while running ANCOMBC2 HOT 2
- Interpreting negative lfc values for "intercept" in primary result
- Installing ANCOMBC HOT 2
- Continuous variable as main variable of interest
- Different results with ancombc2 depending on the order of the taxa
- Visualization the output of ancombc2
- Pseudo-count sensitivity testing when no pseudo-counts are added
- Error in { : task 1 failed - "values must be length 1, but FUN(X[[2]]) result is length 0"
- Help with ancombc2 analysis with repeated measures
- Extract normalised counts for linear models outside of ANCOMBC?
- Failure to install ANCOMBC neither windows nor Ubuntu HOT 1
- global test and pairwise comparisons giving pvals of all NA or all 1
- Feature Request: Support for Using Taxa as Explanatory Variables in ANCOMBC2
- "Error: subscript contains invalid names" when running ancombc2 HOT 3
- Interpreting error when running ancombc2 function: Error in is.infinite(o1) : default method not implemented for type 'list'
- NAs and 1s in ancombc2 primary result table HOT 1
- object 'passed_ss_age' not found
- Testing interactions: global test using F test with approximate degrees of freedom instead of LRT
- Error for specific dataset when using rand_formula "contrasts can be applied only to factors with 2 or more levels"
- q-values (adjusted p-values) too low for continuous variable
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from ancombc.