Marc Sturm

OpenMS – An open-source software framework for mass spectrometry

BackgroundMass spectrometry is an essential analytical technique for high-throughput analysis in proteomics and metabolomics. The development of new separation techniques, precise mass analyzers and experimental protocols is a very active field of research. This leads to more complex experimental setups yielding ever increasing amounts of data. Consequently, analysis of the data is currently often the bottleneck for experimental studies. Although software tools for many data analysis tasks are available today, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow.ResultsWe present OpenMS, a software framework for rapid application development in mass spectrometry. OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis. This has already been demonstrated in several studies.ConclusionOpenMS is available under the Lesser GNU Public License (LGPL) from the project website at http://www.openms.de.

Guidelines for diagnostic next generation sequencing

We present, on behalf of EuroGentest and the European Society of Human Genetics, guidelines for the evaluation and validation of next-generation sequencing (NGS) applications for the diagnosis of genetic disorders. The work was performed by a group of laboratory geneticists and bioinformaticians, and discussed with clinical geneticists, industry and patients’ representatives, and other stakeholders in the field of human genetics. The statements that were written during the elaboration of the guidelines are presented here. The background document and full guidelines are available as supplementary material. They include many examples to assist the laboratories in the implementation of NGS and accreditation of this service. The work and ideas presented by others in guidelines that have emerged elsewhere in the course of the past few years were also considered and are acknowledged in the full text. Interestingly, a few new insights that have not been cited before have emerged during the preparation of the guidelines. The most important new feature is the presentation of a ‘rating system’ for NGS-based diagnostic tests. The guidelines and statements have been applauded by the genetic diagnostic community, and thus seem to be valuable for the harmonization and quality assurance of NGS diagnostics in Europe.

OptiType: precision HLA typing from next-generation sequencing data

Motivation: The human leukocyte antigen (HLA) gene cluster plays a crucial role in adaptive immunity and is thus relevant in many biomedical applications. While next-generation sequencing data are often available for a patient, deducing the HLA genotype is difficult because of substantial sequence similarity within the cluster and exceptionally high variability of the loci. Established approaches, therefore, rely on specific HLA enrichment and sequencing techniques, coming at an additional cost and extra turnaround time. Result: We present OptiType, a novel HLA genotyping algorithm based on integer linear programming, capable of producing accurate predictions from NGS data not specifically enriched for the HLA cluster. We also present a comprehensive benchmark dataset consisting of RNA, exome and whole-genome sequencing data. OptiType significantly outperformed previously published in silico approaches with an overall accuracy of 97% enabling its use in a broad range of applications. Contact: szolek@informatik.uni-tuebingen.de Supplementary information: Supplementary data are available at Bioinformatics online.

An Automated Pipeline for High-Throughput Label-Free Quantitative Proteomics

We present a computational pipeline for the quantification of peptides and proteins in label-free LC-MS/MS data sets. The pipeline is composed of tools from the OpenMS software framework and is applicable to the processing of large experiments (50+ samples). We describe several enhancements that we have introduced to OpenMS to realize the implementation of this pipeline. They include new algorithms for centroiding of raw data, for feature detection, for the alignment of multiple related measurements, and a new tool for the calculation of peptide and protein abundances. Where possible, we compare the performance of the new algorithms to that of their established counterparts in OpenMS. We validate the pipeline on the basis of two small data sets that provide ground truths for the quantification. There, we also compare our results to those of MaxQuant and Progenesis LC-MS, two popular alternatives for the analysis of label-free data. We then show how our software can be applied to a large heterogeneous data set of 58 LC-MS/MS runs.

Next-generation sequencing in X-linked intellectual disability

X-linked intellectual disability (XLID) is a genetically heterogeneous disorder with more than 100 genes known to date. Most genes are responsible for a small proportion of patients only, which has hitherto hampered the systematic screening of large patient cohorts. We performed targeted enrichment and next-generation sequencing of 107 XLID genes in a cohort of 150 male patients. Hundred patients had sporadic intellectual disability, and 50 patients had a family history suggestive of XLID. We also analysed a sporadic female patient with severe ID and epilepsy because she had strongly skewed X-inactivation. Target enrichment and high parallel sequencing allowed a diagnostic coverage of >10 reads for ~96% of all coding bases of the XLID genes at a mean coverage of 124 reads. We found 18 pathogenic variants in 13 XLID genes (AP1S2, ATRX, CUL4B, DLG3, IQSEC2, KDM5C, MED12, OPHN1, SLC9A6, SMC1A, UBE2A, UPF3B and ZDHHC9) among the 150 male patients. Thirteen pathogenic variants were present in the group of 50 familial patients (26%), and 5 pathogenic variants among the 100 sporadic patients (5%). Systematic gene dosage analysis for low coverage exons detected one pathogenic hemizygous deletion. An IQSEC2 nonsense variant was detected in the female ID patient, providing further evidence for a role of this gene in encephalopathy in females. Skewed X-inactivation was more frequently observed in mothers with pathogenic variants compared with those without known X-linked defects. The mutation rate in the cohort of sporadic patients corroborates previous estimates of 5–10% for X-chromosomal defects in male ID patients.

TOPPView: an open-source viewer for mass spectrometry data.

Visualization of complex mass spectrometric data sets is becoming increasingly important in proteomics and metabolomics. We present TOPPView, an integrated data visualization and analysis tool for mass spectrometric data sets. TOPPView allows the visualization and comparison of individual mass spectra, two-dimensional LC-MS data sets and their accompanying metadata. By supporting standardized XML-based data exchange formats, data import is possible from any type of mass spectrometer. The integrated analysis tools of the OpenMS Proteomics Pipeline (TOPP) allow efficient data analysis from within TOPPView through a convenient graphical user interface. TOPPView runs on all major operating systems and is available free of charge under an open-source license at http://www.openms.de.

TOPPAS: a graphical workflow editor for the analysis of high-throughput proteomics data.

Mass spectrometry coupled to high-performance liquid chromatography (HPLC-MS) is evolving more quickly than ever. A wide range of different instrument types and experimental setups are commonly used. Modern instruments acquire huge amounts of data, thus requiring tools for an efficient and automated data analysis. Most existing software for analyzing HPLC-MS data is monolithic and tailored toward a specific application. A more flexible alternative consists of pipeline-based tool kits allowing the construction of custom analysis workflows from small building blocks, e.g., the Trans Proteomics Pipeline (TPP) or The OpenMS Proteomics Pipeline (TOPP). One drawback, however, is the hurdle of setting up complex workflows using command line tools. We present TOPPAS, The OpenMS Proteomics Pipeline ASsistant, a graphical user interface (GUI) for rapid composition of HPLC-MS analysis workflows. Workflow construction reduces to simple drag-and-drop of analysis tools and adding connections in between. Integration of external tools into these workflows is possible as well. Once workflows have been developed, they can be deployed in other workflow management systems or batch processing systems in a fully automated fashion. The implementation is portable and has been tested under Windows, Mac OS X, and Linux. TOPPAS is open-source software and available free of charge at http://www.OpenMS.de/TOPPAS .

SYNE1 ataxia is a common recessive ataxia with major non-cerebellar features: a large multi-centre study

Mutations in the synaptic nuclear envelope protein 1 (SYNE1) gene have been reported to cause a relatively pure, slowly progressive cerebellar recessive ataxia mostly identified in Quebec, Canada. Combining next-generation sequencing techniques and deep-phenotyping (clinics, magnetic resonance imaging, positron emission tomography, muscle histology), we here established the frequency, phenotypic spectrum and genetic spectrum of SYNE1 in a screening of 434 non-Canadian index patients from seven centres across Europe. Patients were screened by whole-exome sequencing or targeted panel sequencing, yielding 23 unrelated families with recessive truncating SYNE1 mutations (23/434 = 5.3%). In these families, 35 different mutations were identified, 34 of them not previously linked to human disease. While only 5/26 patients (19%) showed the classical SYNE1 phenotype of mildly progressive pure cerebellar ataxia, 21/26 (81%) exhibited additional complicating features, including motor neuron features in 15/26 (58%). In three patients, respiratory dysfunction was part of an early-onset multisystemic neuromuscular phenotype with mental retardation, leading to premature death at age 36 years in one of them. Positron emission tomography imaging confirmed hypometabolism in extra-cerebellar regions such as the brainstem. Muscle biopsy reliably showed severely reduced or absent SYNE1 staining, indicating its potential use as a non-genetic indicator for underlying SYNE1 mutations. Our findings, which present the largest systematic series of SYNE1 patients and mutations outside Canada, revise the view that SYNE1 ataxia causes mainly a relatively pure cerebellar recessive ataxia and that it is largely limited to Quebec. Instead, complex phenotypes with a wide range of extra-cerebellar neurological and non-neurological dysfunctions are frequent, including in particular motor neuron and brainstem dysfunction. The disease course in this multisystemic neurodegenerative disease can be fatal, including premature death due to respiratory dysfunction. With a relative frequency of ∼5%, SYNE1 is one of the more common recessive ataxias worldwide.

Erratum: Guidelines for diagnostic next-generation sequencing

Correction to: European Journal of Human Genetics (2016) 24, 2–5; doi:10.1038/ejhg.2015.226; published online 28 October 2015 Following the publication of this article, the authors wish to append a Supplementary file. This information can be found on European Journal of Human Genetics website http://www.

A statistical learning approach to the modeling of chromatographic retention of oligonucleotides incorporating sequence and secondary structure data

We propose a new model for predicting the retention time of oligonucleotides. The model is based on ν support vector regression using features derived from base sequence and predicted secondary structure of oligonucleotides. Because of the secondary structure information, the model is applicable even at relatively low temperatures where the secondary structure is not suppressed by thermal denaturing. This makes the prediction of oligonucleotide retention time for arbitrary temperatures possible, provided that the target temperature lies within the temperature range of the training data. We describe different possibilities of feature calculation from base sequence and secondary structure, present the results and compare our model to existing models.