@article{WolfKuonenDandekaretal.2015,
  author    = {Wolf, Beat and Kuonen, Pierre and Dandekar, Thomas and Atlan, David},
  title     = {DNAseq workflow in a diagnostic context and an example of a user friendly implementation},
  series = {BioMed Research International},
  journal   = {BioMed Research International},
  number    = {403497},
  doi       = {10.1155/2015/403497},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-144527},
  year      = {2015},
  abstract  = {Over recent years next generation sequencing (NGS) technologies evolved from costly tools used by very few, to a much more accessible and economically viable technology. Through this recently gained popularity, its use-cases expanded from research environments into clinical settings. But the technical know-how and infrastructure required to analyze the data remain an obstacle for a wider adoption of this technology, especially in smaller laboratories. We present GensearchNGS, a commercial DNAseq software suite distributed by Phenosystems SA. The focus of GensearchNGS is the optimal usage of already existing infrastructure, while keeping its use simple. This is achieved through the integration of existing tools in a comprehensive software environment, as well as custom algorithms developed with the restrictions of limited infrastructures in mind. This includes the possibility to connect multiple computers to speed up computing intensive parts of the analysis such as sequence alignments. We present a typical DNAseq workflow for NGS data analysis and the approach GensearchNGS takes to implement it. The presented workflow goes from raw data quality control to the final variant report. This includes features such as gene panels and the integration of online databases, like Ensembl for annotations or Cafe Variome for variant sharing.},
  language  = {en}
}
@article{SickelAnkenbrandGrimmeretal.2015,
  author    = {Sickel, Wiebke and Ankenbrand, Markus J. and Grimmer, Gudrun and Holzschuh, Andrea and H{\"a}rtel, Stephan and Lanzen, Jonathan and Steffan-Dewenter, Ingolf and Keller, Alexander},
  title     = {Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach},
  series = {BMC Ecology},
  volume    = {15},
  journal   = {BMC Ecology},
  number    = {20},
  doi       = {10.1186/s12898-015-0051-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-125730},
  year      = {2015},
  abstract  = {Background Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing. Results We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinations of forward and reverse identifiers attached to the barcode marker allow high sample throughput with a single sequencing run. It does not require further adapter ligation steps after amplification. We applied this protocol to 384 pollen samples collected by solitary bees and sequenced all samples together on a single Illumina MiSeq v2 flow cell. According to rarefaction curves, 2,000-3,000 high quality reads per sample were sufficient to assess the complete diversity of 95\% of the samples. We were able to detect 650 different plant taxa in total, of which 95\% were classified at the species level. Together with the laboratory protocol, we also present an update of the reference database used by the classifier software, which increases the total number of covered global plant species included in the database from 37,403 to 72,325 (93\% increase). Conclusions This study thus offers improvements for the laboratory and bioinformatical workflow to existing approaches regarding data quantity and quality as well as processing effort and cost-effectiveness. Although only tested for pollen samples, it is furthermore applicable to other research questions requiring plant identification in mixed and challenging samples.},
  language  = {en}
}