@article{HammerBanckAmbergetal.2010, author = {Hammer, Paul and Banck, Michaela S. and Amberg, Ronny and Wang, Cheng and Petznick, Gabriele and Luo, Shujun and Khrebtukova, Irina and Schroth, Gary P. and Beyerlein, Peter and Beutler, Andreas S.}, title = {mRNA-seq with agnostic splice site discovery for nervous system transcriptomics tested in chronic pain}, series = {Genome Research}, volume = {20}, journal = {Genome Research}, number = {6}, issn = {1549-5469}, doi = {10.1101/gr.101204.109}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-6446}, pages = {15}, year = {2010}, abstract = {mRNA-seq is a paradigm-shifting technology because of its superior sensitivity and dynamic range and its potential to capture transcriptomes in an agnostic fashion, i.e., independently of existing genome annotations. Implementation of the agnostic approach, however, has not yet been fully achieved. In particular, agnostic mapping of pre-mRNA splice sites has not been demonstrated. The present study pursued dual goals: (1) to advance mRNA-seq bioinformatics toward unbiased transcriptome capture and (2) to demonstrate its potential for discovery in neuroscience by applying the approach to an in vivo model of neurological disease. We have performed mRNA-seq on the L4 dorsal root ganglion (DRG) of rats with chronic neuropathic pain induced by spinal nerve ligation (SNL) of the neighboring (L5) spinal nerve. We found that 12.4\% of known genes were induced and 7\% were suppressed in the dysfunctional (but anatomically intact) L4 DRG 2 wk after SNL. These alterations persisted chronically (2 mo). Using a read cluster classifier with strong test characteristics (ROC area 97\%), we discovered 10,464 novel exons. A new algorithm for agnostic mapping of pre-mRNA splice junctions (SJs) achieved a precision of 97\%. Integration of information from all mRNA-seq read classes including SJs led to genome reannotations specifically relevant for the species used (rat), the anatomical site studied (DRG), and the neurological disease considered (pain); for example, a 64-exon coreceptor for the nociceptive transmitter substance P was identified, and 21.9\% of newly discovered exons were shown to be dysregulated. Thus, mRNA-seq with agnostic analysis methods appears to provide a highly productive approach for in vivo transcriptomics in the nervous system.}, language = {en} } @article{PetrilloFabbriKagklietal.2021, author = {Petrillo, Mauro and Fabbri, M and Kagkli, Dafni Maria and Querci, Maddalena and Van den Eede, Guy and Alm, Erik and Aytan-Aktug, Derya and Capella-Gutierrez, Salvador and Carrillo, Catherine and Cestaro, Alessandro and Chan, Kok-Gan and Coque, Teresa and Endrullat, Christoph and Gut, Ivo and Hammer, Paul and Kay, Gemma L. and Madec, Jean-Yves and Mather, Alison E. and McHardy, Alice Carolyn and Naas, Thierry and Paracchini, Valentina and Peter, Silke and Pightling, Arthur and Raffael, Barbara and Rossen, John and Rupp{\´e}, Etienne and Schlaberg, Robert and Vanneste, Kevin and Weber, Lukas M. and Westh, Henrik and Angers-Loustau, Alexandre}, title = {A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing [version 1; peer review: 2 approved with reservations]}, series = {F1000Research}, journal = {F1000Research}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-15699}, year = {2021}, abstract = {Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain "live" (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines' implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.}, language = {en} }