Quality control was performed on each raw fastq file with FastQC and results were then aggregated with MultiQC.
View ReportDada2 belongs to the denoisers algorithm family. It aims at retrieving and counting the occurence of true biological sequences at a single nucleotide resolution. The dada2 Qiime2 plugin outputs statistics about the number of reads lost at each step of the algorithm. The non-chimeric columns shows how many reads are kept at the end of the process.
If too many reads are lost, it is likely that something went wrong. Please refer to the Inspect denoising stats section of the wiki for more explanations.
Denoisers output is an Amplicon Sequence Variant (ASV) table that indicates how many times each ASV has been observed in each sample.
View SummaryQiime2 give stats about sequences length and provide links to blast a sequence against the NCBI nt database.
ASV identifiers are md5 hash of the representative sequence. A FASTA file linking identifiers and sequences can be found here
Rarefaction consists in subsampling all samples to a given sampling depth, in order to account for different sampling sizes. Diversity analysis within Qiime2 are performed after rarefaction. Alpha rarefaction curves show the alpha diversity as a function of the sampling depth, and allows to select a rarefaction threshold that will maximize the alpha diversity while minimizing the number of discarded samples (because of low sample size).
View CurvesAlpha diversity refers to the intra sample diversity. There are several ways to measure it such as the number of observed species, Shannon diversity (that takes abundance into account) or Faith phylogenetic diversity.
Alpha diversity measures can be found in a table here
Qiime2 test for statistical significant differences in terms of alpha diversity between conditions.
View Shannon View Eveness View Faith View Observed OTUsBeta diversity refers to the inter sample diversity. There are several distances used to measure it such as Bray-Curtis or Unifrac.
Beta diversity distances can be found in tables here
Qiime2 builds PCoA plots that allows to visualize the distances between samples.
View Bray-Curtis View Jaccard View Unweighted Unifrac View Weighted UnifracBeta group significance allows to determine if differences among groups are significant. Default method is PERMANOVA
View Bray-Curtis View Jaccard View Unweighted Unifrac View Weighted UnifracTaxonomic composition at different levels and association taxonomy/ASV identifiers.
View Taxonomic Composition View Taxons