TY  - JOUR
A1  - Pluta, Natalie
A1  - Hoffjan, Sabine
A1  - Zimmer, Frederic
A1  - Köhler, Cornelia
A1  - Lücke, Thomas
A1  - Mohr, Jennifer
A1  - Vorgerd, Matthias
A1  - Nguyen, Hoa Huu Phuc
A1  - Atlan, David
A1  - Wolf, Beat
A1  - Zaum, Ann-Kathrin
A1  - Rost, Simone
T1  - Homozygous inversion on chromosome 13 involving SGCG detected by short read whole genome sequencing in a patient suffering from limb-girdle muscular dystrophy
JF  - Genes
N2  - New techniques in molecular genetic diagnostics now allow for accurate diagnosis in a large proportion of patients with muscular diseases. Nevertheless, many patients remain unsolved, although the clinical history and/or the muscle biopsy give a clear indication of the involved genes. In many cases, there is a strong suspicion that the cause must lie in unexplored gene areas, such as deep-intronic or other non-coding regions. In order to find these changes, next-generation sequencing (NGS) methods are constantly evolving, making it possible to sequence entire genomes to reveal these previously uninvestigated regions. Here, we present a young woman who was strongly suspected of having a so far genetically unsolved sarcoglycanopathy based on her clinical history and muscle biopsy. Using short read whole genome sequencing (WGS), a homozygous inversion on chromosome 13 involving SGCG and LINC00621 was detected. The breakpoint in intron 2 of SGCG led to the absence of γ-sarcoglycan, resulting in the manifestation of autosomal recessive limb-girdle muscular dystrophy 5 (LGMDR5) in the young woman.
KW  - inversion
KW  - sarcoglycanopathy
KW  - whole genome sequencing (WGS)
KW  - next generation sequencing (NGS)
KW  - LGMDR5
KW  - muscle disease
KW  - genetic diagnostics
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-288122
SN  - 2073-4425
VL  - 13
IS  - 10
ER  - 
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  -