Merge branch 'master' of github.com:adrientaudiere/MiscMetabar

DESCRIPTION

@@ -95,8 +95,8 @@ Remotes:
     github::adrientaudiere/lulu,
     github::david-barnett/microViz,
     github::erocoar/gghalves,
-    bioc::release/phyloseq,
-    bioc::release/dada2,
+    bioc::phyloseq,
+    bioc::dada2,
     github::brendanf/FUNGuildR
 Config/testthat/edition: 3
 Config/testthat/parallel: true

paper/paper.bib

@@ -1,4 +1,4 @@
-@article{altschul1990,
+@article{altschul1990,
   doi       = {10.32388/rhq6vj},
   title     = {Basic local alignment search tool},
   author    = {Altschul, Stephen F and Gish, Warren and Miller, Webb and Myers, Eugene W and Lipman, David J},
@@ -300,4 +300,4 @@ @article{xu2023
   number    = {2},
   year      = {2023},
   publisher = {Elsevier}
-}
+}

paper/paper.md

@@ -62,6 +62,9 @@ The filter functions `subset_samples_pq()` and `subset_taxa_pq()` complement `su
 
 I also implement a function to filter taxa based on their blast to a custom database (`filter_asv_blast()`). This function uses the blastn software [@altschul1990] to compare ASV sequences to a database and filter out species that are below a given threshold of e-value and/or bit-score.
 
+### Post-clustering
+
+Several pipelines use at least two step of clustering. The function `asv2otu()`, using either the `DECIPHER::Clusterize()` function from R or the [vsearch](https://github.com/torognes/vsearch) software allow to recluster existing groups such as **ASV** (stands for *Amplicon Sequence Variant*) obtained by the `dada2::dada()` function (see the vignette [reclustering](https://adrientaudiere.github.io/MiscMetabar/articles/Reclustering.html)).  Another transformation method is implemented in `lulu_pq()`, which uses @froslev2017's method for post-clustering curation of DNA amplicon data. Note that a fast and robust C++ re-implementation of lulu called [mumu](https://github.com/frederic-mahe/mumu) [@mahe2023] is also available through the function `mumu_pq()`.
 
 ## Exploration 
 
@@ -79,4 +82,4 @@ The targets R package [@landau2021] improves the efficiency and reproducibility
 
 I thank Will Landau, Paul McMurdie, and Benjamin Callahan for their excellent R packages on which `MiscMetabar` rests. I also want to acknowledge Franck Richard, Lise Roy, Élisa Taschen and the [Mycea](https://mycea.fr/) team for the discussion and work around metabarcoding.
 
-# References
+# References