Fall 2019: Investigating the Microbial Communities in Mortality Composts (5/8) -- BIT 477/577 Metagenomics

Fall 2019: Investigating the Microbial Communities in Mortality Composts 5 Data visualization with R. BIT 477/577 Fall 2019 Students and Carlos Goller Learning Objectives - To perform basic data analyses using QIIME and a downloaded dataset. - Given a formatted dataset and an appropriate visualization tool, the participant will be able to accurately summarize the output for different measures of diversity. - Explain the UniFrac metric of distance and diversity. - Interpret and evaluate a 2D representation of multidimensional data (ordination plot) - Visualize metagenomic data with Phyloseq UniFrac - Unique Fraction Metric (Unifrac) measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. https://aem.asm.org/content/71/12/8228 PhyloSeq Ordination plot- visualization of beta diversity for identification of possible data structures. - PCoA is the most commonly used plot for microbiome data - Can be obtained via R and Phyloseq - Ordination guide for Phyloseq: https://joey711.github.io/phyloseq/plot_ordination-examples.html Main points of Article #3 Nowinski et al. (2019). Microbial metagenomes and metatranscriptomes during a coastal phytoplankton bloom. Scientific Data. 6. Article number: 129. The authors used metatranscriptomics, pipelines, RNAseq, Illumina, DADA2 for this study. - Sampling was performed using an Environmental Sample Processor (ESP) which provides on-site (in situ) collection and analysis of water samples from the ocean. - The ESP had two filters: 5.0 uM pore for eukaryotic organisms and 0.22 uM pore to capture bacterial and archaeal microbes. - Environmental information/measurements were also taken by a CTD (conductivity, temperature, and depth) instrument mounted on the ESP. - They constructed relative abundance of bacterial and archaeal maps by family. - Also constructed relative abundance of eukaryotic tax maps - Why/how did they validate the study? - Quality control: removed contaminants by removing and filtering of reads - - - BBDuk software - - Validated to other similar datasets by microbial community standards - Used spike on controls- used to calibrate abundance organisms by amount of water filtered - - - - Calculate relative abundance normalized by volume. - - This study focused mainly on methods; missing results and discussion. It is a data descriptor article, which provides the scientific community with elaborative information and “high-quality materials data” to be able to understand and use in further research.