TY  - JOUR
A1  - Wolf, Beat
A1  - Kuonen, Pierre
A1  - Dandekar, Thomas
A1  - Atlan, David
T1  - DNAseq workflow in a diagnostic context and an example of a user friendly implementation
JF  - BioMed Research International
N2  - 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.
KW  - next generation sequencing
KW  - genome browser
KW  - mutation
KW  - algorithm
KW  - database
KW  - format
KW  - discovery
KW  - exome
KW  - variants
KW  - alignment
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-144527
IS  - 403497
ER  - 
TY  - JOUR
A1  - Kunz, Meik
A1  - Wolf, Beat
A1  - Schulze, Harald
A1  - Atlan, David
A1  - Walles, Thorsten
A1  - Walles, Heike
A1  - Dandekar, Thomas
T1  - Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools
JF  - Genes
N2  - Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs.
KW  - lung cancer
KW  - non-invasive biomarkers
KW  - miRNAs
KW  - lncRNAs
KW  - bioinformatics
KW  - early diagnosis
KW  - algorithm
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147990
VL  - 8
IS  - 1
ER  -