BackgroundRNA-seq has been a boon to the quantitative analysis of transcriptomes. A notable application is the detection of changes in transcript usage between experimental conditions. For example, discovery of pathological alternative splicing may allow the development of new treatments or better management of patients. From an analysis perspective, there are several ways to approach RNA-seq data to unravel differential transcript usage, such as annotation-based exon-level counting, differential analysis of the percentage spliced in, or quantitative analysis of assembled transcripts. The goal of this research is to compare and contrast current state-of-the-art methods, and to suggest improvements to commonly used work flows.ResultsWe assess the performance of representative work flows using synthetic data and explore the effect of using non-standard counting bin definitions as input to DEXSeq, a state-of-the-art inference engine. Although the canonical counting provided the best results overall, several non-canonical approaches were as good or better in specific aspects and most counting approaches outperformed the evaluated event- and assembly-based methods. We show that an incomplete annotation catalog can have a detrimental effect on the ability to detect differential transcript usage in transcriptomes with few isoforms per gene and that isoform-level prefiltering can considerably improve false discovery rate control.ConclusionCount-based methods generally perform well in the detection of differential transcript usage. Controlling the false discovery rate at the imposed threshold is difficult, particularly in complex organisms, but can be improved by prefiltering the annotation catalog.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0862-3) contains supplementary material, which is available to authorized users.

Background: More people than ever before are currently living with a diagnosis of cancer and the number of people concerned is likely to continue to rise. Cancer survivors are at risk of developing a second primary cancer (SPC). This study aims to investigate the risk of SPC in Switzerland. Methods: The study cohort included all patients with a first primary cancer recorded in 9 Swiss population-based cancer registries 1981-2009 who had a minimum survival of 6 months, and a potential follow-up until the end of 2014. We calculated standardized incidence ratios (SIR) to estimate relative risks (RR) of SPC in cancer survivors compared with the cancer risk of the general population. SIR were stratified by type of first cancer, sex, age and period of first diagnosis, survival period and site of SPC. Results: A total of 33,793 SPC were observed in 310,113 cancer patients. Both male (SIR 1.18, 95%CI 1.16-1.19) and female (SIR 1.20, 95%CI 1.18-1.22) cancer survivors had an elevated risk of developing a SPC. Risk estimates varied substantially according to type of first cancer and were highest in patients initially diagnosed with cancer of the oral cavity and pharynx, Hodgkin lymphoma, laryngeal, oesophageal, or lung cancer. Age-stratified analyses revealed a tendency towards higher RR in patients first diagnosed at younger ages. Stratified by survival period, risk estimates showed a rising trend with increasing time from the initial diagnosis. We observed strong associations between particular types of first and SPC, i.e. cancer types sharing common risk factors such as smoking or alcohol consumption (e.g. repeated cancer of the oral cavity and pharynx (SIR males 20.12, 95%CI 17.91-22.33; SIR females 37.87, 95%CI 30.27-45.48). Conclusion: Swiss cancer survivors have an increased risk of developing a SPC compared to the general population, particularly patients first diagnosed before age 50 and those surviving more than 10 years. Cancer patients should remain under continued surveillance not only for recurrent cancers but also for new cancers. Some first and SPCs share lifestyle associated risk factors making it important to promote healthier lifestyles in both the general population and cancer survivors.

BackgroundCancer of unknown primary (CUP) is a distinct clinicopathological entity with poor prognosis, frequently resistant to chemotherapy. Comprehensive genomic profiling (CGP) by next‐generation sequencing potentially identifies novel treatment options for CUP patients. The objective of this study was to determine incidence and survival trends and to discuss the value of CGP in CUP patients.MethodsAge‐standardized incidence rates (ASR) per 100 000 were calculated for 2935 CUP patients from 1981 to 2014 using cancer registry data of the canton of Zurich, Switzerland. Kaplan–Meier survival curves were estimated for sex, age, and histological groups. Cox proportional hazards regression models were used to estimate adjusted hazard ratios (HR). A literature review was conducted to assess the current use of CGP in CUP patients.ResultsASR of CUP increased from 10.3 to 17.6 between 1981 and 1997 and decreased to 5.8/100 000 in 2014. Mean overall survival remained stable. Mortality was significantly lower for patients with squamous cell carcinoma (HR 0.48 [95% CI, 0.41‐0.57]) and neuroendocrine carcinoma (0.75 [0.63‐0.88]) and higher for unclassified neoplasms (1.25 [1.13‐1.66]) compared to adenocarcinomas. The literature review identified 10 studies using CGP of CUP tissue. Clinically relevant mutations were identified in up to 85% of CUP patients, of which 13%‐64% may benefit from currently available drugs.ConclusionsCUP incidence decreased probably due to improved diagnostics, but mortality did not improve over the last 34 years. CGP testing may help to identify molecular signatures in CUP patients and enable targeted treatment.

The present study investigates behavioral and electrophysiological auditory and cognitive-related plasticity in three groups of healthy older adults (60-77 years). Group 1 was moderately hearing-impaired, experienced hearing aid users, and fitted with new hearing aids using non-linear frequency compression (NLFC on); Group 2, also moderately hearing-impaired, used the same type of hearing aids but NLFC was switched off during the entire period of study duration (NLFC off); Group 3 represented individuals with age-appropriate hearing (NHO) as controls, who were not different in IQ, gender, or age from Group 1 and 2. At five measurement time points (M1-M5) across three months, a series of active oddball tasks were administered while EEG was recorded. The stimuli comprised syllables consisting of naturally high-pitched fricatives (/sh/, /s/, and /f/), which are hard to distinguish for individuals with presbycusis. By applying a data-driven microstate approach to obtain global field power (GFP) as a measure of processing effort, the modulations of perceptual (P50, N1, P2) and cognitive-related (N2b, P3b) auditory evoked potentials were calculated and subsequently related to behavioral changes (accuracy and reaction time) across time. All groups improved their performance across time, but NHO showed consistently higher accuracy and faster reaction times than the hearing-impaired groups, especially under difficult conditions. Electrophysiological results complemented this finding by demonstrating longer latencies in the P50 and the N1 peak in hearing aid users. Furthermore, the GFP of cognitive-related evoked potentials decreased from M1 to M2 in the NHO group, while a comparable decrease in the hearing-impaired group was only evident at M5. After twelve weeks of hearing aid use of eight hours each day, we found a significantly lower GFP in the P3b of the group with NLFC on as compared to the group with NLFC off. These findings suggest higher processing effort, as evidenced by higher GFP, in hearing-impaired individuals when compared to those with normal hearing, although the hearing-impaired show a decrease of processing effort after repeated stimulus exposure. In addition, our findings indicate that the acclimatization to a new hearing aid algorithm may take several weeks.

This study compares the excess mortality impact of the COVID-19 pandemic in 2020 with that of other pandemics and mortality events dating back more than 100 years in Switzerland, Sweden, and Spain—3 European countries that have reliable continuous data on death counts and were militarily neutral during both world wars.

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Data quality is an important issue in cancer registration. This paper provides a comprehensive overview of the four main data quality indicators (comparability, validity, timeliness, and completeness) for the Cancer Registry Zurich and Zug (Switzerland). We extracted all malignant cancer cases (excluding non-melanoma skin cancer) diagnosed between 1980 and 2014 in the canton of Zurich. Methods included the proportion of morphologically verified cases (MV%), the proportion of DCN and DCO cases (2009–2014), cases with primary site uncertain (PSU%), the stability of incidence rates over time, age-specific incidence rates for childhood cancer, and mortality:incidence (MI) ratios. The DCO rate decreased from 6.4% in 1997 to 0.8% in 2014 and was <5% since 2000. MV% was 95.5% in 2014. PSU% was <3% over the whole period. The incidence rate of all tumours increased over time with site-specific fluctuations. The overall M:I ratio decreased from 0.58 in 1980 to 0.37 in 2014. Overall, data quality of the Cancer Registry Zurich and Zug was acceptable according to the methods presented in this review. Most indicators improved over time with low DCO rates, high MV%, low PSU%, relatively low M:I ratios and age-specific incidence of childhood cancer within reference ranges.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article.