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Biological studies, especially in ecology, health sciences and taxonomy, need to describe the biological composition of samples. During the last twenty years, (i) the development of DNA sequencing, (ii) reference databases, (iii) high-throughput sequencing (HTS), and (iv) bioinformatics resources have allowed the description of biological communities through metabarcoding. Metabarcoding involves the sequencing of millions (meta-) of short regions of specific DNA (-barcoding, Valentini, Pompanon, and Taberlet (2009)) often from environmental samples (eDNA, Taberlet et al. (2012)) such as human stomach contents, lake water, soil and air.

MiscMetabar aims to facilitate the description, transformation, exploration and reproducibility of metabarcoding analysis using R. The development of MiscMetabar relies heavily on the R packages dada2, phyloseq and targets.


There is no CRAN or bioconductor version of MiscMetabar for now (work in progress).

You can install the stable version from GitHub with:


You can install the developement version from GitHub with:

devtools::install_github("adrientaudiere/MiscMetabar", ref = "dev")

Some use of MiscMetabar

See vignettes in the MiscMetabar website for more examples.

Summarize a physeq object

Alpha-diversity analysis

p <- MiscMetabar::hill_pq(data_fungi, variable = "Height")
#> Taxa are now in rows.
#> Cleaning suppress 0 taxa and 0 samples.
Hill number 1

Hill number 1

Result of the Tuckey post-hoc test

Result of the Tuckey post-hoc test

Beta-diversity analysis

ggvenn_pq(data_fungi, fact = "Height") +
  ggplot2::scale_fill_distiller(palette = "BuPu", direction = 1) +
  labs(title = "Share number of ASV among Height in tree")

Installation of other softwares for debian Linux distributions


sudo apt-get install ncbi-blast+


sudo apt-get install vsearch
Taberlet, Pierre, Eric Coissac, Mehrdad Hajibabaei, and Loren H Rieseberg. 2012. “Environmental Dna.” Molecular Ecology. Wiley Online Library.
Valentini, Alice, François Pompanon, and Pierre Taberlet. 2009. “DNA Barcoding for Ecologists.” Trends in Ecology & Evolution 24 (2): 110–17.