Here we have gathered some literature on metabarcoding.
- Zinger et al. 2019. DNA metabarcoding—Need for robust experimental designs to draw sound ecological conclusions. Molecular Ecology, 28, 1857-1862
- Deiner et al. 2017. Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Molecular Ecology, 26, 5872-5895.
- Bohmann et al. 2014 . Environmental DNA for wildlife biology and biodiversity monitoring. TREE, 29.
- Alberdi et al. 2017. Scrutinizing key steps for reliable metabarcoding of environmental samples. Methods in Ecology and Evolution, 9, 134-147.
- Ficetola et al. 2016. How to limit false positives in environmental DNA and metabarcoding? Molecular Ecology, 16, 604-607.
- Dickie et al. 2018. Towards robust and repeatable sampling methods ineDNA-based studies. Molecular Ecology Resources, 18, 940-952. Schnell et al. 2015. Tag jumps illuminated – reducing sequence‐to‐sample misidentifications in metabarcoding studies. Molecular Ecology Resources, 15, 1289-1303.
- Antich et al. 2021. To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography. BMC Bioinformatics, 22,177.
- Lamb et al. 2019. How quantitative is metabarcoding: A meta‐analytical approach. Molecular Ecology, 28, 420-430.
- Jamy et al. 2019. Long-read metabarcoding of the eukaryotic rDNA operon to phylogenetically and taxonomically resolve environmental diversity. Molecular Ecology Resources, 20, 429-443.
- Foster et al. 2017. Metacoder: An R package for visualization and manipulation of community taxonomic diversity data. PLoS Computational biology, 13.
- Rognes et al. 2016. VSEARCH: a versatile open source tool for metagenomics. PeerJ
- Mahe et al. 2015. Swarm v2: highly-scalable and high-resolution amplicon clustering. PeerJ
- Callahan et al. 2016. DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 13, 581-588.
- Barbera et al. 2019. EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences. Systematic Biology, 68, 365-369.
- Deiner et al. 2016 - Environmental DNA reveals that rivers are conveyer belts of biodiversity information. Nat. Com
- Röttjers et al. 2018 - From hairballs to hypotheses–biological insights from microbial networks. FEMS Microbiology Reviews, 42, 761–780
- Layeghifard et al.2017 - Disentangling Interactions in the Microbiome: A Network Perspective. Trend. Microbiol.
- Faust et al. 2012 Microbial interactions: from networks to models. Nat. rev. Microb.