Übersicht

Vogler, A. P., & Monaghan, M. T. (2007). Recent advances in DNA taxonomy. Journal of Zoological Systematics and Evolutionary Research, 45(July), 1–10.
http://doi.org/10.1111/j.1439-0469.2006.00384.x
Pereira, F., Carneiro, J., & Amorim, A. (2008). Identification of species with DNA-based technology: current progress and challenges. Recent Patents on DNA & Gene Sequences, 2, 187–199.
http://doi.org/10.2174/187221508786241738

Tools

Classification Resources for Environmental Sequence Tags (CREST)
- Lanzén, A., Jørgensen, S. L., Huson, D. H., Gorfer, M., Grindhaug, S. H., Jonassen, I., … Urich, T. (2012). CREST--classification resources for environmental sequence tags. PloS One, 7(11), e49334.
  http://doi.org/10.1371/journal.pone.0049334
- CREST (Classification Resources for Environmnetal Sequence Tags) is a collection of resources for taxonomical classification of high throughput sequencing. CREST utilises a curated taxonomy derived from taxonomic annotation of a global alignment of phylogenetic marker genes.
Quantitative Insights Into Microbial Ecology (QIIME)
- Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., … others. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 7(5), 335–336.
- QIIME is an open-source bioinformatics pipeline for performing microbiome analysis from raw DNA sequencing data. QIIME is designed to take users from raw sequencing data generated on the Illumina or other platforms through publication quality graphics and statistics. This includes demultiplexing and quality filtering, OTU picking, taxonomic assignment, and phylogenetic reconstruction, and diversity analyses and visualizations. QIIME has been applied to studies based on billions of sequences from tens of thousands of samples.
- Tutorial: Fungal ITS analysis tutorial (an IPython Notebook): open-reference OTU picking
mothur
- Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., … Weber, C. F. (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75(23), 7537–41.
  http://doi.org/10.1128/AEM.01541-09
- This project seeks to develop a single piece of open-source, expandable software to fill the bioinformatics needs of the microbial ecology community. In February 2009 we released the first version of mothur, which had accelerated versions of the popular DOTUR and SONS programs. Since then we have added the functionality of a number of other popular tools. mothur is currently the most cited bioinformatics tool for analyzing 16S rRNA gene sequences.