Analysis on the 6-tree Alpha Beta diversity, alphabeta

Analysis on the 6-tree Alpha Beta diversity, alphabeta
Preparations before analysis

# Go To The working directory cd example_PE250

Review in the previous section: Our OTU obtains the species annotation and learns the various operations of the OTU table-adding information, format conversion, and filtering information. Next we will learn how to analyze the evolution of the OTU sequence and calculate the Alpha and Beta diversity values at the same time. 16. The tree building tree is based on the multi-sequence comparison results, which can display a wealth of information. We will explain it in detail in the R plot. This is just an input file for Alpha and Beta diversity analysis.

# Clustalo multi-sequence comparison, if not, install Clustal Omegaclustalo-I result/rep_seqs4.fa-o temp/empty -- seqtype = DNA -- full -- force -- threads = 30 # conservative sequence and conservative region filter_alignment.py-I in the filter results temp/rep_seqs_align.fa-o temp/# rep_seqs_align_pfiltered.fa, only very short conserved region saved # make_phylogeny.py-I temp/rep_seqs_align_pfiltered.fasta-o result/rep_seqs.tree # generate tree by fasttree Based on FastTree

17. Alpha diversity is used to calculate the composition of species in the sample, including quantity and richness. The specific explanation is as follows: the expansion sub-chart interprets a box of line charts: The OTU table needs to be standardized Before Alpha diversity computing, because the number of detected species varies with the sequencing depth. We re-sample The OTU table to the same data volume to fairly compare the species of each sample. The method is as follows:

# View the minimum data size of a sample biom summarize-table-I result/otu_table4.biom # standardize single_rarefaction.py-I result/otu_table4.biom-o temp/daily-d 2797 # commonly used computing four Alpha diversity indexes: alpha_diversity.py-I temp/otu_table_rare.biom-o result/alpha.txt-t result/rep_seqs.tree-m shannon, chao1, observed_otus, PD_whole_tree

18. Beta diversity is calculated for the same or different samples, and OTU tables also need to be standardized. Too much information is lost using the sampling method, which is not conducive to statistics. In this step, we select the CSS standardization method.

# CSS standardization OTU table normalize_table.py-I result/otu_table4.biom-o temp/otu_table_css.biom-a CSS # convert the standardized OTU table to text, used to draw biom convert-I temp/otu_table_css.biom-o result/otu_table_css.txt -- table-type = "OTU table" -- to-tsv # Delete unnecessary table information, it is convenient for R to read sed-I '/# Const/d; s/# OTU // g; s/ID. // g'result/otu_table_css.txt # Calculate the Beta diversity beta_diversity.py-I temp/otu_table_css.biom-o result/beta/-t result/rep_seqs.tree-m bray_curtis, weighted_unirac, unweighted_unifrac # Sort the Beta diversity distance files to facilitate R reading sed-I's/^ \ t // G' result/beta /*