Learn about statistical analysis of microbiome data, including alpha diversity, beta diversity, and differential abundance using R and the phyloseq package
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Microbiome Analysis
metagenomics
Learn about the various techniques to study the micorbiome, including 16s rRNA sequencing, metagenomics, metatranscriptomics, and proteomics.
metagenomics
Demo of METAGENOTE for annotating samples with metadata, use of ontologies during annotation and submission of data & metadata to NCBI's SRA.
metagenomics
Learn about shotgun metagenomics through pipeline WGSA2 on NIAID's web application Nephele
metagenomics
Publishing to NCBI SRA the Easy Way Using METAGENOTE
metagenomics
Metagenomics overview (Metataxonomics)
metagenomics
Learn how to use NIAID's web application Nephele for QC of any genomics data and further analysis of microbiome data (16S and shotgun metagenomics)
metagenomics
Metagenomics overview (Shotgun metagenomics)
metagenomics
Learn about shotgun metagenomics with a visual and interactive community exploration software MEGAN6-CE
metagenomics
16S rRNA MicrobioLearn about 16S rRNA amplicon-based microbiome data and how to process it! We will go over the basics and benefits of amplicon sequencing data, and use R’s Divisive Amplicon Denoising Algorithm 2 (DADA2) package to turn sequencing data into a table of counts that can be used for downstream analysis (which we will cover in another training!). You will learn about adapter and primer trimming, quality checks, chimeras, and much more. You are welcome to bring your own data to experiment with, but some will be made available as well.me Analysis: Sequence Data Processing
metagenomics
Viral metagenomics. A hands-on workshop using NIAID's HPC Locus, but is also suitable for anyone who wants to learn about tools for viral discovery and viral diversity analysis using metagenomics.
metagenomics
Learn about 16S rRNA amplicon-based microbiome data and how to process it! We will go over the basics and benefits of amplicon sequencing data, and use R’s Divisive Amplicon Denoising Algorithm 2 (DADA2) package to turn sequencing data into a table of counts that can be used for downstream analysis (which we will cover in another training!). You will learn about adapter and primer trimming, quality checks, chimeras, and much more. You are welcome to bring your own data to experiment with, but some will be made available as well.