Anaconda - Targeted Differential and Global Enrichment Analysis of
Taxonomic Rank by Shared Asvs
Targeted differential and global enrichment analysis of
taxonomic rank by shared ASVs (Amplicon Sequence Variant), for
high-throughput eDNA sequencing of fungi, bacteria, and
metazoan. Actually works in two steps: I) Targeted differential
analysis from QIIME2 data and II) Global analysis by Taxon
Mann-Whitney U test analysis from targeted analysis (I) (I)
Estimate variance-mean dependence in count/abundance ASVs data
from high-throughput sequencing assays and test for
differential represented ASVs based on a model using the
negative binomial distribution. (II) NCBITaxon_MWU uses
continuous measure of significance (such as fold-change or
-log(p-value)) to identify NCBITaxon that are significantly
enriches with either up- or down-represented ASVs. If the
measure is binary (0 or 1) the script will perform a typical
'NCBITaxon enrichment' analysis based Fisher's exact test: it
will show NCBITaxon over-represented among the ASVs that have 1
as their measure. On the plot, different fonts are used to
indicate significance and color indicates enrichment with
either up (red) or down (blue) regulated ASVs. No colors are
shown for binary measure analysis. The tree on the plot is
hierarchical clustering of NCBITaxon based on shared ASVs.
Categories with no branch length between them are subsets of
each other. The fraction next to the category name indicates
the fraction of 'good' ASVs in it; 'good' ASVs are the ones
exceeding the arbitrary absValue cutoff (option in
taxon_mwuPlot()). For Fisher's based test, specify
absValue=0.5. This value does not affect statistics and is used
for plotting only. The original idea was for genes differential
expression analysis from Wright et al (2015)
<doi:10.1186/s12864-015-1540-2>; adapted here for taxonomic
analysis. The 'Anaconda' package makes it possible to carry out
these analyses by automatically creating several graphs and
tables and storing them in specially created subfolders. You
will need your QIIME2 pipeline output for each kingdom (eg;
Fungi and/or Bacteria and/or Metazoan): i) taxonomy.tsv, ii)
taxonomy_RepSeq.tsv, iii) ASV.tsv and iv)
SampleSheet_comparison.txt (the latter being created by you).
