This amplicon sequencing analysis workflow is fully written in R. It is based on [Dada2](https://pubmed.ncbi.nlm.nih.gov/27214047/) amplicon sequence variants to reveal microbial communities and [Phyloseq](https://joey711.github.io/phyloseq/index.html) R objects to handle datas.
rANOMALY improvements:
- A versatile and customizable workflow, from fastq treatment to statistical analysis.
- Integrating contaminant filtering based on control samples with decontam R package.
- Taxonomic assignment based on IDTAXA, and the abilitie to merge annotation from two databases, with validation step to keep the best assignment.
- Alpha and beta diversity indexes are compared between conditions with integrated statistical analysis (ANOVA, permanova and non-parametric test).
- Three main differential analysis methods ([DESeq2](https://bioconductor.org/packages/release/bioc/html/DESeq2.html), [Metacoder](https://grunwaldlab.github.io/metacoder_documentation/), [metagenomeSeq](https://bioconductor.org/packages/release/bioc/html/metagenomeSeq.html)) are integrated to decipher differences between communities composition.