Microbiome

Denoising Amplicon Sequence Variants Using DADA2, DeBlur, and UNOISE3 with QIIME2

Below I provide scripts to implement several workflows for denoising 16s rRNA gene sequences used by the Microbial Metagenomics Analysis Center (MMAC) at CCHMC for paired-end data. These scripts are written to run on the CCHMC high-performance computing (HPC) cluster.

Profiling of Shotgun Metagenomic Sequence Data using Kraken2/Bracken and HUMAnN2

Below I provide scripts to implement the current default workflow for taxonomic profiling using Kraken2 and Bracken and functional profiling using HUMAnN2 used by the Microbial Metagenomics Analysis Center (MMAC) at CCHMC for paired-end data.

Observation Weights for Differential Abundance of Zero-Inflated Microbiome Data with DESeq2

I recently read through Calgaro et. al. “Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data” where they examined the performance of statistical models developed for bulk RNA (RNA-seq), single-cell RNA-seq (scRNA-seq), and microbial metagenomics to:

Denoising Amplicon Sequence Data Using USEARCH and UNOISE3

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.

Downloading Amplicon Sequence Runs from the NCBI SRA

A collaborator recently asked if I could help pull down a few thousand sequence files from the NCBI Sequence Read Archive (SRA) for a secondary analysis. This is a short post primarily to help me (and hopefully others) remember how to do this once you have a set of SRR IDs of interest.

Introduction to Phyloseq

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.

Introduction to the Statistical Analysis of Microbiome Data in R

This post is also from the Introduction to Metagenomics Summer Workshop and provides a quick introduction to some common analytic methods used to analyze microbiome data. I thought it might be of interest to a broader audience so decided to post it here.

Introduction to Microbiome Data Analysis

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 …

Introduction to Denoising Amplicon Sequence Data in R

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 …

Recent Advancements in the Statistical Analysis of Microbial Metagenomic Sequence Data

These slides are from an invited talk I gave to the Division of Gastroenterology, Hepatology and Nutrition at CCHMC as part of their Digestive Health Center Seminar Series. Topics covered in this talk include an introduction to denoising amplicon …