Previously, I shared some workflows for denoising 16S rRNA gene sequence data used by our lab. One of the examples used the popular UNOISE3 algorithm developed by Robert Edgar and implemented in USEARCH.
I recently analyzed some data from an experiment with a pre-post study design where our estimands of interest were the baseline adjusted mean difference in Shannon diversity and species differential abundance between arms at post-treatment.
Microbiome studies often seek to identify individual features (i.e., OTUs/ASVs, species, pathways, etc.) associated some condition (i.e., exposure, experimental treatment, etc.) of interest. This problem can be approached in many different ways, but most commonly, one-at-a-time (OaaT) feature screening is undertaken.
Below I provide scripts to implement the current default workflow for taxonomic and functional profiling using the Huttenhower Lab’s Biobakery Tool Suite used by the Microbial Metagenomics Analysis Center (MMAC) at CCHMC for paired-end data.
During the Introduction to Metagenomics Summer Workshop we discussed denoising amplicon sequence variants and worked through Ben Callahan’s DADA2 tutorial. During that session, I mentioned several other approaches and algorithms for denoising or clustering amplicon sequence data including UNOISE3, DeBlur and Mothur.
This post is from a tutorial demonstrating the processing of amplicon short read data in R taught as part of the Introduction to Metagenomics Summer Workshop. It provides a quick introduction some of the functionality provided by phyloseq and follows some of Paul McMurdie’s excellent tutorials.
This was a talk given as part of the UC-CCHMC introductory workshop covering the basics of microbial metagenomic sequence data processing and statistical analysis. Topics covered in this talk include an introduction to challenging features of …
This was a talk given as part of the UC-CCHMC introductory workshop covering the basics of microbial metagenomic sequence data processing and statistical analysis. Topics covered include an introduction to denoising 16S rRNA gene sequencing data, a …