90-lab.Rmd.Rmd

---
title: "Questions for Lab 1, 2 and 3"
author: "Leo lahti & Rajesh Shigdel"
date: Sys.time()
output: html_document
---

The example in this tutorial are mainly based on this online book by Leo Lahti [aut], Sudarsan Shetty [aut], Felix GM Ernst [aut, cre]        
[Orchestrating Microbiome Analysis](https://microbiome.github.io/OMA/)

In this tutorila we use [human gastrointestinal microbiota data](https://www.microbiomeatlas.org/)



   #Lab 1
   
1.Make a se (SummarizedExperiment) Object for the further analysis 

 
2.Once you make a SummarizedExperiment object out of this data then check how many taxa and samples the data contains? 


3.Report how many unique phylum present in this data


4. Subset the data at the phylum level with only taking bacterial phyla that are greater than 10% of prevalence in the total sample (feature selection lab 1)


5. Subset a se object which consist only two phyum i.e Actinobacteria", "Cyanobacteria

 
6. Calculates relative abundances, and stores the table to assays


7.Perform a centred log-ratio transformation (clr)

* Aitchison, J. (1986). “The Statistical Analysis of Compositional Data”, Chapman and Hall, reprinted in 2003 with additional material by The Blackburn Press 


8.calculate Abundances of all taxa in specific sample and abundance of specific taxa in all samples




                    #Lab 2 
  
                   ##Clustering and visualization
                   
 1. Visualize Beta-diversity using principal coordinate analysis (PCoA); use relative abundance data with bray-Curtis dissimilarities


2.  Visualize Beta-diversity using principal coordinate analysis (PCoA); with Aitchison distance (clr transformation+ Euclidean distance)


 3. Cluster the samples using Dirichlet- multinomial mixture model 


 4. Visualize the cluster in the PCoA plot




                #Lab 3 
                
                ##Analysis and interpretation 

 1. What taxa are driving the axis? Calculate the spearman correlation between PC1 and the relative abundance of the bacteria and visualize the results in a bar plot.


 2. Visualize the dominant taxonomic group of each sample by colour on PCoA plot 

 3. Visualize gender by colour on PCoA plot