Dataset Information

Quality control and quantification in IG/TR next-generation sequencing marker identification: protocols and bioinformatic functionalities by EuroClonality-NGS.

ABSTRACT: Assessment of clonality, marker identification and measurement of minimal residual disease (MRD) of immunoglobulin (IG) and T cell receptor (TR) gene rearrangements in lymphoid neoplasms using next-generation sequencing (NGS) is currently under intensive development for use in clinical diagnostics. So far, however, there is a lack of suitable quality control (QC) options with regard to standardisation and quality metrics to ensure robust clinical application of such approaches. The EuroClonality-NGS Working Group has therefore established two types of QCs to accompany the NGS-based IG/TR assays. First, a central polytarget QC (cPT-QC) is used to monitor the primer performance of each of the EuroClonality multiplex NGS assays; second, a standardised human cell line-based DNA control is spiked into each patient DNA sample to work as a central in-tube QC and calibrator for MRD quantification (cIT-QC). Having integrated those two reference standards in the ARResT/Interrogate bioinformatic platform, EuroClonality-NGS provides a complete protocol for standardised IG/TR gene rearrangement analysis by NGS with high reproducibility, accuracy and precision for valid marker identification and quantification in diagnostics of lymphoid malignancies.

SUBMITTER: Knecht H

PROVIDER: S-EPMC6756032 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Quality control and quantification in IG/TR next-generation sequencing marker identification: protocols and bioinformatic functionalities by EuroClonality-NGS.

Knecht Henrik H Reigl Tomas T Kotrová Michaela M Appelt Franziska F Stewart Peter P Bystry Vojtech V Krejci Adam A Grioni Andrea A Pal Karol K Stranska Kamila K Plevova Karla K Rijntjes Jos J Songia Simona S Svatoň Michael M Froňková Eva E Bartram Jack J Scheijen Blanca B Herrmann Dietrich D García-Sanz Ramón R Hancock Jeremy J Moppett John J van Dongen Jacques J M JJM Cazzaniga Giovanni G Davi Frédéric F Groenen Patricia J T A PJTA Hummel Michael M Macintyre Elizabeth A EA Stamatopoulos Kostas K Trka Jan J Langerak Anton W AW Gonzalez David D Pott Christiane C Brüggemann Monika M Darzentas Nikos N

Leukemia 20190621 9

Assessment of clonality, marker identification and measurement of minimal residual disease (MRD) of immunoglobulin (IG) and T cell receptor (TR) gene rearrangements in lymphoid neoplasms using next-generation sequencing (NGS) is currently under intensive development for use in clinical diagnostics. So far, however, there is a lack of suitable quality control (QC) options with regard to standardisation and quality metrics to ensure robust clinical application of such approaches. The EuroClonality ...[more]

PMID: 31227779

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Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

Project description:Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems; in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystem's incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways; reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise; and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions; the environment in which the interaction takes place must also be explicitly defined. Our framework provides a natural representation of nonlinear interaction phenomena, and will therefore be an important tool for modelling large-scale evolved or synthetic biomolecular networks.

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Dataset Information

Quality control and quantification in IG/TR next-generation sequencing marker identification: protocols and bioinformatic functionalities by EuroClonality-NGS.

Publications

Quality control and quantification in IG/TR next-generation sequencing marker identification: protocols and bioinformatic functionalities by EuroClonality-NGS.

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